---
_id: '14711'
abstract:
- lang: eng
  text: "In nature, different species find their niche in a range of environments,
    each with its unique characteristics. While some thrive in uniform (homogeneous)
    landscapes where environmental conditions stay relatively consistent across space,
    others traverse the complexities of spatially heterogeneous terrains. Comprehending
    how species are distributed and how they interact within these landscapes holds
    the key to gaining insights into their evolutionary dynamics while also informing
    conservation and management strategies.\r\n\r\nFor species inhabiting heterogeneous
    landscapes, when the rate of dispersal is low compared to spatial fluctuations
    in selection pressure, localized adaptations may emerge. Such adaptation in response
    to varying selection strengths plays an important role in the persistence of populations
    in our rapidly changing world. Hence, species in nature are continuously in a
    struggle to adapt to local environmental conditions, to ensure their continued
    survival. Natural populations can often adapt in time scales short enough for
    evolutionary changes to influence ecological dynamics and vice versa, thereby
    creating a feedback between evolution and demography. The analysis of this feedback
    and the relative contributions of gene flow, demography, drift, and natural selection
    to genetic variation and differentiation has remained a recurring theme in evolutionary
    biology. Nevertheless, the effective role of these forces in maintaining variation
    and shaping patterns of diversity is not fully understood. Even in homogeneous
    environments devoid of local adaptations, such understanding remains elusive.
    Understanding this feedback is crucial, for example in determining the conditions
    under which extinction risk can be mitigated in peripheral populations subject
    to deleterious mutation accumulation at the edges of species’ ranges\r\nas well
    as in highly fragmented populations.\r\n\r\nIn this thesis we explore both uniform
    and spatially heterogeneous metapopulations, investigating and providing theoretical
    insights into the dynamics of local adaptation in the latter and examining the
    dynamics of load and extinction as well as the impact of joint ecological and
    evolutionary (eco-evolutionary) dynamics in the former. The thesis is divided
    into 5 chapters.\r\n\r\nChapter 1 provides a general introduction into the subject
    matter, clarifying concepts and ideas used throughout the thesis. In chapter 2,
    we explore how fast a species distributed across a heterogeneous landscape adapts
    to changing conditions marked by alterations in carrying capacity, selection pressure,
    and migration rate.\r\n\r\nIn chapter 3, we investigate how migration selection
    and drift influences adaptation and the maintenance of variation in a metapopulation
    with three habitats, an extension of previous models of adaptation in two habitats.
    We further develop analytical approximations for the critical threshold required
    for polymorphism to persist.\r\n\r\nThe focus of chapter 4 of the thesis is on
    understanding the interplay between ecology and evolution as coupled processes.
    We investigate how eco-evolutionary feedback between migration, selection, drift,
    and demography influences eco-evolutionary outcomes in marginal populations subject
    to deleterious mutation accumulation. Using simulations as well as theoretical
    approximations of the coupled dynamics of population size and allele frequency,
    we analyze how gene flow from a large mainland source influences genetic load
    and population size on an island (i.e., in a marginal population) under genetically
    realistic assumptions. Analyses of this sort are important because small isolated
    populations, are repeatedly affected by complex interactions between ecological
    and evolutionary processes, which can lead to their death. Understanding these
    interactions can therefore provide an insight into the conditions under which
    extinction risk can be mitigated in peripheral populations thus, contributing
    to conservation and restoration efforts.\r\n\r\nChapter 5 extends the analysis
    in chapter 4 to consider the dynamics of load (due to deleterious mutation accumulation)
    and extinction risk in a metapopulation. We explore the role of gene flow, selection,
    and dominance on load and extinction risk and further pinpoint critical thresholds
    required for metapopulation persistence.\r\n\r\nOverall this research contributes
    to our understanding of ecological and evolutionary mechanisms that shape species’
    persistence in fragmented landscapes, a crucial foundation for successful conservation
    efforts and biodiversity management."
acknowledged_ssus:
- _id: SSU
alternative_title:
- ISTA Thesis
article_processing_charge: No
author:
- first_name: Oluwafunmilola O
  full_name: Olusanya, Oluwafunmilola O
  id: 41AD96DC-F248-11E8-B48F-1D18A9856A87
  last_name: Olusanya
  orcid: 0000-0003-1971-8314
date_created: 2023-12-26T22:49:53Z
date_published: 2024-01-19T00:00:00Z
date_updated: 2025-05-26T09:05:10Z
day: '19'
ddc:
- '576'
degree_awarded: MS
department:
- _id: NiBa
- _id: GradSch
doi: 10.15479/at:ista:14711
ec_funded: 1
file:
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has_accepted_license: '1'
language:
- iso: eng
license: https://creativecommons.org/licenses/by-nc-sa/4.0/
month: '01'
oa: 1
oa_version: Published Version
page: '183'
project:
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
  grant_number: '665385'
  name: International IST Doctoral Program
- _id: c08d3278-5a5b-11eb-8a69-fdb09b55f4b8
  grant_number: P32896
  name: Causes and consequences of population fragmentation
- _id: 34c872fe-11ca-11ed-8bc3-8534b82131e6
  grant_number: '26380'
  name: Polygenic Adaptation in a Metapopulation
publication_identifier:
  issn:
  - 2663 - 337X
publication_status: published
publisher: Institute of Science and Technology Austria
related_material:
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    relation: part_of_dissertation
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  - id: '10787'
    relation: part_of_dissertation
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  - id: '14732'
    relation: part_of_dissertation
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status: public
supervisor:
- first_name: Nicholas H
  full_name: Barton, Nicholas H
  id: 4880FE40-F248-11E8-B48F-1D18A9856A87
  last_name: Barton
  orcid: 0000-0002-8548-5240
- first_name: Jitka
  full_name: Polechova, Jitka
  last_name: Polechova
- first_name: Himani
  full_name: Sachdeva, Himani
  last_name: Sachdeva
title: Local adaptation, genetic load and extinction in metapopulations
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  short: CC BY-NC-SA (4.0)
type: dissertation
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2024'
...
---
_id: '14821'
alternative_title:
- ISTA Thesis
article_processing_charge: No
author:
- first_name: Heloisa
  full_name: Chiossi, Heloisa
  id: 2BBA502C-F248-11E8-B48F-1D18A9856A87
  last_name: Chiossi
citation:
  ama: Chiossi HSC. Adaptive hierarchical representations in the hippocampus. 2024.
    doi:<a href="https://doi.org/10.15479/at:ista:14821">10.15479/at:ista:14821</a>
  apa: Chiossi, H. S. C. (2024). <i>Adaptive hierarchical representations in the hippocampus</i>.
    Institute of Science and Technology Austria. <a href="https://doi.org/10.15479/at:ista:14821">https://doi.org/10.15479/at:ista:14821</a>
  chicago: Chiossi, Heloisa S. C. “Adaptive Hierarchical Representations in the Hippocampus.”
    Institute of Science and Technology Austria, 2024. <a href="https://doi.org/10.15479/at:ista:14821">https://doi.org/10.15479/at:ista:14821</a>.
  ieee: H. S. C. Chiossi, “Adaptive hierarchical representations in the hippocampus,”
    Institute of Science and Technology Austria, 2024.
  ista: Chiossi HSC. 2024. Adaptive hierarchical representations in the hippocampus.
    Institute of Science and Technology Austria.
  mla: Chiossi, Heloisa S. C. <i>Adaptive Hierarchical Representations in the Hippocampus</i>.
    Institute of Science and Technology Austria, 2024, doi:<a href="https://doi.org/10.15479/at:ista:14821">10.15479/at:ista:14821</a>.
  short: H.S.C. Chiossi, Adaptive Hierarchical Representations in the Hippocampus,
    Institute of Science and Technology Austria, 2024.
date_created: 2024-01-16T14:25:21Z
date_published: 2024-01-19T00:00:00Z
date_updated: 2024-02-01T09:50:29Z
day: '19'
ddc:
- '570'
degree_awarded: PhD
department:
- _id: GradSch
- _id: JoCs
doi: 10.15479/at:ista:14821
ec_funded: 1
file:
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  date_updated: 2024-01-19T11:03:59Z
  embargo: 2025-01-19
  embargo_to: open_access
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  file_size: 6567275
  relation: main_file
file_date_updated: 2024-01-19T11:04:05Z
has_accepted_license: '1'
language:
- iso: eng
month: '01'
oa_version: Published Version
page: '89'
project:
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
  grant_number: '665385'
  name: International IST Doctoral Program
publication_identifier:
  issn:
  - 2663 - 337X
publication_status: published
publisher: Institute of Science and Technology Austria
status: public
supervisor:
- first_name: Jozsef L
  full_name: Csicsvari, Jozsef L
  id: 3FA14672-F248-11E8-B48F-1D18A9856A87
  last_name: Csicsvari
  orcid: 0000-0002-5193-4036
title: Adaptive hierarchical representations in the hippocampus
type: dissertation
user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9
year: '2024'
...
---
_id: '15020'
abstract:
- lang: eng
  text: "This thesis consists of four distinct pieces of work within theoretical biology,
    with two themes in common: the concept of optimization in biological systems,
    and the use of information-theoretic tools to quantify biological stochasticity
    and statistical uncertainty.\r\nChapter 2 develops a statistical framework for
    studying biological systems which we believe to be optimized for a particular
    utility function, such as retinal neurons conveying information about visual stimuli.
    We formalize such beliefs as maximum-entropy Bayesian priors, constrained by the
    expected utility. We explore how such priors aid inference of system parameters
    with limited data and enable optimality hypothesis testing: is the utility higher
    than by chance?\r\nChapter 3 examines the ultimate biological optimization process:
    evolution by natural selection. As some individuals survive and reproduce more
    successfully than others, populations evolve towards fitter genotypes and phenotypes.
    We formalize this as accumulation of genetic information, and use population genetics
    theory to study how much such information can be accumulated per generation and
    maintained in the face of random mutation and genetic drift. We identify the population
    size and fitness variance as the key quantities that control information accumulation
    and maintenance.\r\nChapter 4 reuses the concept of genetic information from Chapter
    3, but from a different perspective: we ask how much genetic information organisms
    actually need, in particular in the context of gene regulation. For example, how
    much information is needed to bind transcription factors at correct locations
    within the genome? Population genetics provides us with a refined answer: with
    an increasing population size, populations achieve higher fitness by maintaining
    more genetic information. Moreover, regulatory parameters experience selection
    pressure to optimize the fitness-information trade-off, i.e. minimize the information
    needed for a given fitness. This provides an evolutionary derivation of the optimization
    priors introduced in Chapter 2.\r\nChapter 5 proves an upper bound on mutual information
    between a signal and a communication channel output (such as neural activity).
    Mutual information is an important utility measure for biological systems, but
    its practical use can be difficult due to the large dimensionality of many biological
    channels. Sometimes, a lower bound on mutual information is computed by replacing
    the high-dimensional channel outputs with decodes (signal estimates). Our result
    provides a corresponding upper bound, provided that the decodes are the maximum
    posterior estimates of the signal."
acknowledged_ssus:
- _id: ScienComp
alternative_title:
- ISTA Thesis
article_processing_charge: No
author:
- first_name: Michal
  full_name: Hledik, Michal
  id: 4171253A-F248-11E8-B48F-1D18A9856A87
  last_name: Hledik
citation:
  ama: Hledik M. Genetic information and biological optimization. 2024. doi:<a href="https://doi.org/10.15479/at:ista:15020">10.15479/at:ista:15020</a>
  apa: Hledik, M. (2024). <i>Genetic information and biological optimization</i>.
    Institute of Science and Technology Austria. <a href="https://doi.org/10.15479/at:ista:15020">https://doi.org/10.15479/at:ista:15020</a>
  chicago: Hledik, Michal. “Genetic Information and Biological Optimization.” Institute
    of Science and Technology Austria, 2024. <a href="https://doi.org/10.15479/at:ista:15020">https://doi.org/10.15479/at:ista:15020</a>.
  ieee: M. Hledik, “Genetic information and biological optimization,” Institute of
    Science and Technology Austria, 2024.
  ista: Hledik M. 2024. Genetic information and biological optimization. Institute
    of Science and Technology Austria.
  mla: Hledik, Michal. <i>Genetic Information and Biological Optimization</i>. Institute
    of Science and Technology Austria, 2024, doi:<a href="https://doi.org/10.15479/at:ista:15020">10.15479/at:ista:15020</a>.
  short: M. Hledik, Genetic Information and Biological Optimization, Institute of
    Science and Technology Austria, 2024.
date_created: 2024-02-23T14:02:04Z
date_published: 2024-02-23T00:00:00Z
date_updated: 2025-06-30T13:21:09Z
day: '23'
ddc:
- '576'
- '519'
department:
- _id: GradSch
- _id: NiBa
- _id: GaTk
doi: 10.15479/at:ista:15020
ec_funded: 1
file:
- access_level: open_access
  checksum: b2d3da47c98d481577a4baf68944fe41
  content_type: application/pdf
  creator: mhledik
  date_created: 2024-02-23T13:50:53Z
  date_updated: 2024-02-23T13:50:53Z
  file_id: '15021'
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  file_size: 14014790
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file_date_updated: 2024-02-23T14:20:16Z
has_accepted_license: '1'
keyword:
- Theoretical biology
- Optimality
- Evolution
- Information
language:
- iso: eng
month: '02'
oa: 1
oa_version: Published Version
page: '158'
project:
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
  grant_number: '665385'
  name: International IST Doctoral Program
- _id: 2665AAFE-B435-11E9-9278-68D0E5697425
  grant_number: RGP0034/2018
  name: Can evolution minimize spurious signaling crosstalk to reach optimal performance?
- _id: bd6958e0-d553-11ed-ba76-86eba6a76c00
  grant_number: '101055327'
  name: Understanding the evolution of continuous genomes
publication_identifier:
  issn:
  - 2663 - 337X
publication_status: published
publisher: Institute of Science and Technology Austria
related_material:
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    relation: part_of_dissertation
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    relation: part_of_dissertation
    status: public
status: public
supervisor:
- first_name: Nicholas H
  full_name: Barton, Nicholas H
  id: 4880FE40-F248-11E8-B48F-1D18A9856A87
  last_name: Barton
  orcid: 0000-0002-8548-5240
- first_name: Gašper
  full_name: Tkačik, Gašper
  id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
  last_name: Tkačik
  orcid: 0000-0002-6699-1455
title: Genetic information and biological optimization
type: dissertation
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2024'
...
---
_id: '14317'
abstract:
- lang: eng
  text: "Markov decision processes can be viewed as transformers of probability distributions.
    While this view is useful from a practical standpoint to reason about trajectories
    of distributions, basic reachability and safety problems are known to be computationally
    intractable (i.e., Skolem-hard) to solve in such models. Further, we show that
    even for simple examples of MDPs, strategies for safety objectives over distributions
    can require infinite memory and randomization.\r\nIn light of this, we present
    a novel overapproximation approach to synthesize strategies in an MDP, such that
    a safety objective over the distributions is met. More precisely, we develop a
    new framework for template-based synthesis of certificates as affine distributional
    and inductive invariants for safety objectives in MDPs. We provide two algorithms
    within this framework. One can only synthesize memoryless strategies, but has
    relative completeness guarantees, while the other can synthesize general strategies.
    The runtime complexity of both algorithms is in PSPACE. We implement these algorithms
    and show that they can solve several non-trivial examples."
acknowledgement: This work was supported in part by the ERC CoG 863818 (FoRM-SMArt)
  and the European Union’s Horizon 2020 research and innovation programme under the
  Marie Skłodowska-Curie Grant Agreement No. 665385 as well as DST/CEFIPRA/INRIA project
  EQuaVE and SERB Matrices grant MTR/2018/00074.
alternative_title:
- LNCS
article_processing_charge: Yes (in subscription journal)
author:
- first_name: S.
  full_name: Akshay, S.
  last_name: Akshay
- first_name: Krishnendu
  full_name: Chatterjee, Krishnendu
  id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
  last_name: Chatterjee
  orcid: 0000-0002-4561-241X
- first_name: Tobias
  full_name: Meggendorfer, Tobias
  id: b21b0c15-30a2-11eb-80dc-f13ca25802e1
  last_name: Meggendorfer
  orcid: 0000-0002-1712-2165
- first_name: Dorde
  full_name: Zikelic, Dorde
  id: 294AA7A6-F248-11E8-B48F-1D18A9856A87
  last_name: Zikelic
  orcid: 0000-0002-4681-1699
citation:
  ama: 'Akshay S, Chatterjee K, Meggendorfer T, Zikelic D. MDPs as distribution transformers:
    Affine invariant synthesis for safety objectives. In: <i>International Conference
    on Computer Aided Verification</i>. Vol 13966. Springer Nature; 2023:86-112. doi:<a
    href="https://doi.org/10.1007/978-3-031-37709-9_5">10.1007/978-3-031-37709-9_5</a>'
  apa: 'Akshay, S., Chatterjee, K., Meggendorfer, T., &#38; Zikelic, D. (2023). MDPs
    as distribution transformers: Affine invariant synthesis for safety objectives.
    In <i>International Conference on Computer Aided Verification</i> (Vol. 13966,
    pp. 86–112). Paris, France: Springer Nature. <a href="https://doi.org/10.1007/978-3-031-37709-9_5">https://doi.org/10.1007/978-3-031-37709-9_5</a>'
  chicago: 'Akshay, S., Krishnendu Chatterjee, Tobias Meggendorfer, and Dorde Zikelic.
    “MDPs as Distribution Transformers: Affine Invariant Synthesis for Safety Objectives.”
    In <i>International Conference on Computer Aided Verification</i>, 13966:86–112.
    Springer Nature, 2023. <a href="https://doi.org/10.1007/978-3-031-37709-9_5">https://doi.org/10.1007/978-3-031-37709-9_5</a>.'
  ieee: 'S. Akshay, K. Chatterjee, T. Meggendorfer, and D. Zikelic, “MDPs as distribution
    transformers: Affine invariant synthesis for safety objectives,” in <i>International
    Conference on Computer Aided Verification</i>, Paris, France, 2023, vol. 13966,
    pp. 86–112.'
  ista: 'Akshay S, Chatterjee K, Meggendorfer T, Zikelic D. 2023. MDPs as distribution
    transformers: Affine invariant synthesis for safety objectives. International
    Conference on Computer Aided Verification. CAV: Computer Aided Verification, LNCS,
    vol. 13966, 86–112.'
  mla: 'Akshay, S., et al. “MDPs as Distribution Transformers: Affine Invariant Synthesis
    for Safety Objectives.” <i>International Conference on Computer Aided Verification</i>,
    vol. 13966, Springer Nature, 2023, pp. 86–112, doi:<a href="https://doi.org/10.1007/978-3-031-37709-9_5">10.1007/978-3-031-37709-9_5</a>.'
  short: S. Akshay, K. Chatterjee, T. Meggendorfer, D. Zikelic, in:, International
    Conference on Computer Aided Verification, Springer Nature, 2023, pp. 86–112.
conference:
  end_date: 2023-07-22
  location: Paris, France
  name: 'CAV: Computer Aided Verification'
  start_date: 2023-07-17
date_created: 2023-09-10T22:01:12Z
date_published: 2023-07-17T00:00:00Z
date_updated: 2025-07-14T09:09:56Z
day: '17'
ddc:
- '000'
department:
- _id: KrCh
doi: 10.1007/978-3-031-37709-9_5
ec_funded: 1
file:
- access_level: open_access
  checksum: f143c8eedf609f20f2aad2eeb496d53f
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  creator: dernst
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  date_updated: 2023-09-20T08:46:43Z
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  file_name: 2023_LNCS_Akshay.pdf
  file_size: 531745
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file_date_updated: 2023-09-20T08:46:43Z
has_accepted_license: '1'
intvolume: '     13966'
language:
- iso: eng
month: '07'
oa: 1
oa_version: Published Version
page: 86-112
project:
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
  grant_number: '665385'
  name: International IST Doctoral Program
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
  call_identifier: H2020
  grant_number: '863818'
  name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
publication: International Conference on Computer Aided Verification
publication_identifier:
  eissn:
  - 1611-3349
  isbn:
  - '9783031377082'
  issn:
  - 0302-9743
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'MDPs as distribution transformers: Affine invariant synthesis for safety objectives'
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  short: CC BY (4.0)
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 13966
year: '2023'
...
---
_id: '14506'
abstract:
- lang: eng
  text: "Payment channel networks are a promising approach to improve the scalability
    bottleneck\r\nof cryptocurrencies. Two design principles behind payment channel
    networks are\r\nefficiency and privacy. Payment channel networks improve efficiency
    by allowing users\r\nto transact in a peer-to-peer fashion along multi-hop routes
    in the network, avoiding\r\nthe lengthy process of consensus on the blockchain.
    Transacting over payment channel\r\nnetworks also improves privacy as these transactions
    are not broadcast to the blockchain.\r\nDespite the influx of recent protocols
    built on top of payment channel networks and\r\ntheir analysis, a common shortcoming
    of many of these protocols is that they typically\r\nfocus only on either improving
    efficiency or privacy, but not both. Another limitation\r\non the efficiency front
    is that the models used to model actions, costs and utilities of\r\nusers are
    limited or come with unrealistic assumptions.\r\nThis thesis aims to address some
    of the shortcomings of recent protocols and algorithms\r\non payment channel networks,
    particularly in their privacy and efficiency aspects. We\r\nfirst present a payment
    route discovery protocol based on hub labelling and private\r\ninformation retrieval
    that hides the route query and is also efficient. We then present\r\na rebalancing
    protocol that formulates the rebalancing problem as a linear program\r\nand solves
    the linear program using multiparty computation so as to hide the channel\r\nbalances.
    The rebalancing solution as output by our protocol is also globally optimal.\r\nWe
    go on to develop more realistic models of the action space, costs, and utilities
    of\r\nboth existing and new users that want to join the network. In each of these
    settings,\r\nwe also develop algorithms to optimise the utility of these users
    with good guarantees\r\non the approximation and competitive ratios."
alternative_title:
- ISTA Thesis
article_processing_charge: No
author:
- first_name: Michelle X
  full_name: Yeo, Michelle X
  id: 2D82B818-F248-11E8-B48F-1D18A9856A87
  last_name: Yeo
  orcid: 0009-0001-3676-4809
citation:
  ama: Yeo MX. Advances in efficiency and privacy in payment channel network analysis.
    2023. doi:<a href="https://doi.org/10.15479/14506">10.15479/14506</a>
  apa: Yeo, M. X. (2023). <i>Advances in efficiency and privacy in payment channel
    network analysis</i>. Institute of Science and Technology Austria. <a href="https://doi.org/10.15479/14506">https://doi.org/10.15479/14506</a>
  chicago: Yeo, Michelle X. “Advances in Efficiency and Privacy in Payment Channel
    Network Analysis.” Institute of Science and Technology Austria, 2023. <a href="https://doi.org/10.15479/14506">https://doi.org/10.15479/14506</a>.
  ieee: M. X. Yeo, “Advances in efficiency and privacy in payment channel network
    analysis,” Institute of Science and Technology Austria, 2023.
  ista: Yeo MX. 2023. Advances in efficiency and privacy in payment channel network
    analysis. Institute of Science and Technology Austria.
  mla: Yeo, Michelle X. <i>Advances in Efficiency and Privacy in Payment Channel Network
    Analysis</i>. Institute of Science and Technology Austria, 2023, doi:<a href="https://doi.org/10.15479/14506">10.15479/14506</a>.
  short: M.X. Yeo, Advances in Efficiency and Privacy in Payment Channel Network Analysis,
    Institute of Science and Technology Austria, 2023.
date_created: 2023-11-10T08:10:43Z
date_published: 2023-11-10T00:00:00Z
date_updated: 2025-07-14T09:09:52Z
day: '10'
ddc:
- '000'
degree_awarded: PhD
department:
- _id: GradSch
- _id: KrPi
doi: 10.15479/14506
ec_funded: 1
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language:
- iso: eng
month: '11'
oa: 1
oa_version: Published Version
page: '162'
project:
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
  grant_number: '665385'
  name: International IST Doctoral Program
publication_identifier:
  issn:
  - 2663 - 337X
publication_status: published
publisher: Institute of Science and Technology Austria
related_material:
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    relation: part_of_dissertation
    status: public
status: public
supervisor:
- first_name: Krzysztof Z
  full_name: Pietrzak, Krzysztof Z
  id: 3E04A7AA-F248-11E8-B48F-1D18A9856A87
  last_name: Pietrzak
  orcid: 0000-0002-9139-1654
title: Advances in efficiency and privacy in payment channel network analysis
type: dissertation
user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9
year: '2023'
...
---
_id: '14510'
acknowledged_ssus:
- _id: EM-Fac
- _id: Bio
- _id: LifeSc
alternative_title:
- ISTA Thesis
article_processing_charge: No
author:
- first_name: Nataliia
  full_name: Gnyliukh, Nataliia
  id: 390C1120-F248-11E8-B48F-1D18A9856A87
  last_name: Gnyliukh
  orcid: 0000-0002-2198-0509
citation:
  ama: Gnyliukh N. Mechanism of clathrin-coated vesicle  formation during endocytosis
    in plants. 2023. doi:<a href="https://doi.org/10.15479/at:ista:14510">10.15479/at:ista:14510</a>
  apa: Gnyliukh, N. (2023). <i>Mechanism of clathrin-coated vesicle  formation during
    endocytosis in plants</i>. Institute of Science and Technology Austria. <a href="https://doi.org/10.15479/at:ista:14510">https://doi.org/10.15479/at:ista:14510</a>
  chicago: Gnyliukh, Nataliia. “Mechanism of Clathrin-Coated Vesicle  Formation during
    Endocytosis in Plants.” Institute of Science and Technology Austria, 2023. <a
    href="https://doi.org/10.15479/at:ista:14510">https://doi.org/10.15479/at:ista:14510</a>.
  ieee: N. Gnyliukh, “Mechanism of clathrin-coated vesicle  formation during endocytosis
    in plants,” Institute of Science and Technology Austria, 2023.
  ista: Gnyliukh N. 2023. Mechanism of clathrin-coated vesicle  formation during endocytosis
    in plants. Institute of Science and Technology Austria.
  mla: Gnyliukh, Nataliia. <i>Mechanism of Clathrin-Coated Vesicle  Formation during
    Endocytosis in Plants</i>. Institute of Science and Technology Austria, 2023,
    doi:<a href="https://doi.org/10.15479/at:ista:14510">10.15479/at:ista:14510</a>.
  short: N. Gnyliukh, Mechanism of Clathrin-Coated Vesicle  Formation during Endocytosis
    in Plants, Institute of Science and Technology Austria, 2023.
date_created: 2023-11-10T09:10:06Z
date_published: 2023-11-10T00:00:00Z
date_updated: 2024-03-25T23:30:25Z
day: '10'
ddc:
- '570'
degree_awarded: PhD
department:
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- _id: JiFr
- _id: MaLo
doi: 10.15479/at:ista:14510
ec_funded: 1
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file_date_updated: 2023-11-23T13:10:55Z
has_accepted_license: '1'
keyword:
- Clathrin-Mediated Endocytosis
- vesicle scission
- Dynamin-Related Protein 2
- SH3P2
- TPLATE complex
- Total internal reflection fluorescence microscopy
- Arabidopsis thaliana
language:
- iso: eng
month: '11'
oa_version: Published Version
page: '180'
project:
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
  grant_number: '665385'
  name: International IST Doctoral Program
publication_identifier:
  isbn:
  - 978-3-99078-037-4
  issn:
  - 2663-337X
publication_status: published
publisher: Institute of Science and Technology Austria
related_material:
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    relation: part_of_dissertation
    status: public
  - id: '9887'
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    relation: part_of_dissertation
    status: public
status: public
supervisor:
- first_name: Jiří
  full_name: Friml, Jiří
  id: 4159519E-F248-11E8-B48F-1D18A9856A87
  last_name: Friml
  orcid: 0000-0002-8302-7596
- first_name: Martin
  full_name: Loose, Martin
  id: 462D4284-F248-11E8-B48F-1D18A9856A87
  last_name: Loose
  orcid: 0000-0001-7309-9724
title: Mechanism of clathrin-coated vesicle  formation during endocytosis in plants
tmp:
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  short: CC BY (4.0)
type: dissertation
user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9
year: '2023'
...
---
_id: '14518'
abstract:
- lang: eng
  text: We consider bidding games, a class of two-player zero-sum graph games. The
    game proceeds as follows. Both players have bounded budgets. A token is placed
    on a vertex of a graph, in each turn the players simultaneously submit bids, and
    the higher bidder moves the token, where we break bidding ties in favor of Player
    1. Player 1 wins the game iff the token visits a designated target vertex. We
    consider, for the first time, poorman discrete-bidding in which the granularity
    of the bids is restricted and the higher bid is paid to the bank. Previous work
    either did not impose granularity restrictions or considered Richman bidding (bids
    are paid to the opponent). While the latter mechanisms are technically more accessible,
    the former is more appealing from a practical standpoint. Our study focuses on
    threshold budgets, which is the necessary and sufficient initial budget required
    for Player 1 to ensure winning against a given Player 2 budget. We first show
    existence of thresholds. In DAGs, we show that threshold budgets can be approximated
    with error bounds by thresholds under continuous-bidding and that they exhibit
    a periodic behavior. We identify closed-form solutions in special cases. We implement
    and experiment with an algorithm to find threshold budgets.
acknowledgement: This research was supported in part by ISF grant no. 1679/21, ERC
  CoG 863818 (FoRM-SMArt) and the European Union’s Horizon 2020 research and innovation
  programme under the Marie SkłodowskaCurie Grant Agreement No. 665385.
article_processing_charge: No
arxiv: 1
author:
- first_name: Guy
  full_name: Avni, Guy
  id: 463C8BC2-F248-11E8-B48F-1D18A9856A87
  last_name: Avni
  orcid: 0000-0001-5588-8287
- first_name: Tobias
  full_name: Meggendorfer, Tobias
  id: b21b0c15-30a2-11eb-80dc-f13ca25802e1
  last_name: Meggendorfer
  orcid: 0000-0002-1712-2165
- first_name: Suman
  full_name: Sadhukhan, Suman
  last_name: Sadhukhan
- first_name: Josef
  full_name: Tkadlec, Josef
  id: 3F24CCC8-F248-11E8-B48F-1D18A9856A87
  last_name: Tkadlec
  orcid: 0000-0002-1097-9684
- first_name: Dorde
  full_name: Zikelic, Dorde
  id: 294AA7A6-F248-11E8-B48F-1D18A9856A87
  last_name: Zikelic
  orcid: 0000-0002-4681-1699
citation:
  ama: 'Avni G, Meggendorfer T, Sadhukhan S, Tkadlec J, Zikelic D. Reachability poorman
    discrete-bidding games. In: <i>Frontiers in Artificial Intelligence and Applications</i>.
    Vol 372. IOS Press; 2023:141-148. doi:<a href="https://doi.org/10.3233/FAIA230264">10.3233/FAIA230264</a>'
  apa: 'Avni, G., Meggendorfer, T., Sadhukhan, S., Tkadlec, J., &#38; Zikelic, D.
    (2023). Reachability poorman discrete-bidding games. In <i>Frontiers in Artificial
    Intelligence and Applications</i> (Vol. 372, pp. 141–148). Krakow, Poland: IOS
    Press. <a href="https://doi.org/10.3233/FAIA230264">https://doi.org/10.3233/FAIA230264</a>'
  chicago: Avni, Guy, Tobias Meggendorfer, Suman Sadhukhan, Josef Tkadlec, and Dorde
    Zikelic. “Reachability Poorman Discrete-Bidding Games.” In <i>Frontiers in Artificial
    Intelligence and Applications</i>, 372:141–48. IOS Press, 2023. <a href="https://doi.org/10.3233/FAIA230264">https://doi.org/10.3233/FAIA230264</a>.
  ieee: G. Avni, T. Meggendorfer, S. Sadhukhan, J. Tkadlec, and D. Zikelic, “Reachability
    poorman discrete-bidding games,” in <i>Frontiers in Artificial Intelligence and
    Applications</i>, Krakow, Poland, 2023, vol. 372, pp. 141–148.
  ista: 'Avni G, Meggendorfer T, Sadhukhan S, Tkadlec J, Zikelic D. 2023. Reachability
    poorman discrete-bidding games. Frontiers in Artificial Intelligence and Applications.
    ECAI: European Conference on Artificial Intelligence vol. 372, 141–148.'
  mla: Avni, Guy, et al. “Reachability Poorman Discrete-Bidding Games.” <i>Frontiers
    in Artificial Intelligence and Applications</i>, vol. 372, IOS Press, 2023, pp.
    141–48, doi:<a href="https://doi.org/10.3233/FAIA230264">10.3233/FAIA230264</a>.
  short: G. Avni, T. Meggendorfer, S. Sadhukhan, J. Tkadlec, D. Zikelic, in:, Frontiers
    in Artificial Intelligence and Applications, IOS Press, 2023, pp. 141–148.
conference:
  end_date: 2023-10-04
  location: Krakow, Poland
  name: 'ECAI: European Conference on Artificial Intelligence'
  start_date: 2023-09-30
date_created: 2023-11-12T23:00:56Z
date_published: 2023-09-28T00:00:00Z
date_updated: 2025-07-14T09:09:57Z
day: '28'
ddc:
- '000'
department:
- _id: ToHe
- _id: KrCh
doi: 10.3233/FAIA230264
ec_funded: 1
external_id:
  arxiv:
  - '2307.15218'
file:
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  checksum: 1390ca38480fa4cf286b0f1a42e8c12f
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  file_size: 501011
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  success: 1
file_date_updated: 2023-11-13T10:16:10Z
has_accepted_license: '1'
intvolume: '       372'
language:
- iso: eng
license: https://creativecommons.org/licenses/by-nc/4.0/
month: '09'
oa: 1
oa_version: Published Version
page: 141-148
project:
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
  grant_number: '665385'
  name: International IST Doctoral Program
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
  call_identifier: H2020
  grant_number: '863818'
  name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
publication: Frontiers in Artificial Intelligence and Applications
publication_identifier:
  isbn:
  - '9781643684369'
  issn:
  - 0922-6389
publication_status: published
publisher: IOS Press
quality_controlled: '1'
scopus_import: '1'
status: public
title: Reachability poorman discrete-bidding games
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type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 372
year: '2023'
...
---
_id: '14539'
abstract:
- lang: eng
  text: "Stochastic systems provide a formal framework for modelling and quantifying
    uncertainty in systems and have been widely adopted in many application domains.
    Formal\r\nverification and control of finite state stochastic systems, a subfield
    of formal methods\r\nalso known as probabilistic model checking, is well studied.
    In contrast, formal verification and control of infinite state stochastic systems
    have received comparatively\r\nless attention. However, infinite state stochastic
    systems commonly arise in practice.\r\nFor instance, probabilistic models that
    contain continuous probability distributions such\r\nas normal or uniform, or
    stochastic dynamical systems which are a classical model for\r\ncontrol under
    uncertainty, both give rise to infinite state systems.\r\nThe goal of this thesis
    is to contribute to laying theoretical and algorithmic foundations\r\nof fully
    automated formal verification and control of infinite state stochastic systems,\r\nwith
    a particular focus on systems that may be executed over a long or infinite time.\r\nWe
    consider formal verification of infinite state stochastic systems in the setting
    of\r\nstatic analysis of probabilistic programs and formal control in the setting
    of controller\r\nsynthesis in stochastic dynamical systems. For both problems,
    we present some of the\r\nfirst fully automated methods for probabilistic (a.k.a.
    quantitative) reachability and\r\nsafety analysis applicable to infinite time
    horizon systems. We also advance the state\r\nof the art of probability 1 (a.k.a.
    qualitative) reachability analysis for both problems.\r\nFinally, for formal controller
    synthesis in stochastic dynamical systems, we present a\r\nnovel framework for
    learning neural network control policies in stochastic dynamical\r\nsystems with
    formal guarantees on correctness with respect to quantitative reachability,\r\nsafety
    or reach-avoid specifications.\r\n"
alternative_title:
- ISTA Thesis
article_processing_charge: No
author:
- first_name: Dorde
  full_name: Zikelic, Dorde
  id: 294AA7A6-F248-11E8-B48F-1D18A9856A87
  last_name: Zikelic
  orcid: 0000-0002-4681-1699
citation:
  ama: Zikelic D. Automated verification and control of infinite state stochastic
    systems. 2023. doi:<a href="https://doi.org/10.15479/14539">10.15479/14539</a>
  apa: Zikelic, D. (2023). <i>Automated verification and control of infinite state
    stochastic systems</i>. Institute of Science and Technology Austria. <a href="https://doi.org/10.15479/14539">https://doi.org/10.15479/14539</a>
  chicago: Zikelic, Dorde. “Automated Verification and Control of Infinite State Stochastic
    Systems.” Institute of Science and Technology Austria, 2023. <a href="https://doi.org/10.15479/14539">https://doi.org/10.15479/14539</a>.
  ieee: D. Zikelic, “Automated verification and control of infinite state stochastic
    systems,” Institute of Science and Technology Austria, 2023.
  ista: Zikelic D. 2023. Automated verification and control of infinite state stochastic
    systems. Institute of Science and Technology Austria.
  mla: Zikelic, Dorde. <i>Automated Verification and Control of Infinite State Stochastic
    Systems</i>. Institute of Science and Technology Austria, 2023, doi:<a href="https://doi.org/10.15479/14539">10.15479/14539</a>.
  short: D. Zikelic, Automated Verification and Control of Infinite State Stochastic
    Systems, Institute of Science and Technology Austria, 2023.
date_created: 2023-11-15T13:39:10Z
date_published: 2023-11-15T00:00:00Z
date_updated: 2025-07-14T09:10:10Z
day: '15'
ddc:
- '000'
degree_awarded: PhD
department:
- _id: KrCh
- _id: GradSch
doi: 10.15479/14539
ec_funded: 1
file:
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language:
- iso: eng
month: '11'
oa: 1
oa_version: Published Version
page: '256'
project:
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
  call_identifier: H2020
  grant_number: '863818'
  name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
  grant_number: '665385'
  name: International IST Doctoral Program
publication_identifier:
  isbn:
  - 978-3-99078-036-7
  issn:
  - 2663 - 337X
publication_status: published
publisher: Institute of Science and Technology Austria
related_material:
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    relation: part_of_dissertation
    status: public
  - id: '12000'
    relation: part_of_dissertation
    status: public
  - id: '12511'
    relation: part_of_dissertation
    status: public
  - id: '14600'
    relation: part_of_dissertation
    status: public
  - id: '14601'
    relation: part_of_dissertation
    status: public
  - id: '9644'
    relation: part_of_dissertation
    status: public
  - id: '10414'
    relation: part_of_dissertation
    status: public
status: public
supervisor:
- first_name: Krishnendu
  full_name: Chatterjee, Krishnendu
  id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
  last_name: Chatterjee
  orcid: 0000-0002-4561-241X
title: Automated verification and control of infinite state stochastic systems
tmp:
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    BY-NC-SA 4.0)
  short: CC BY-NC-SA (4.0)
type: dissertation
user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9
year: '2023'
...
---
_id: '14559'
abstract:
- lang: eng
  text: We consider the problem of learning control policies in discrete-time stochastic
    systems which guarantee that the system stabilizes within some specified stabilization
    region with probability 1. Our approach is based on the novel notion of stabilizing
    ranking supermartingales (sRSMs) that we introduce in this work. Our sRSMs overcome
    the limitation of methods proposed in previous works whose applicability is restricted
    to systems in which the stabilizing region cannot be left once entered under any
    control policy. We present a learning procedure that learns a control policy together
    with an sRSM that formally certifies probability 1 stability, both learned as
    neural networks. We show that this procedure can also be adapted to formally verifying
    that, under a given Lipschitz continuous control policy, the stochastic system
    stabilizes within some stabilizing region with probability 1. Our experimental
    evaluation shows that our learning procedure can successfully learn provably stabilizing
    policies in practice.
acknowledgement: This work was supported in part by the ERC-2020-AdG 101020093, ERC
  CoG 863818 (FoRM-SMArt) and the European Union’s Horizon 2020 research and innovation
  programme under the Marie Skłodowska-Curie Grant Agreement No. 665385.
alternative_title:
- LNCS
article_processing_charge: No
author:
- first_name: Matin
  full_name: Ansaripour, Matin
  last_name: Ansaripour
- first_name: Krishnendu
  full_name: Chatterjee, Krishnendu
  id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
  last_name: Chatterjee
  orcid: 0000-0002-4561-241X
- first_name: Thomas A
  full_name: Henzinger, Thomas A
  id: 40876CD8-F248-11E8-B48F-1D18A9856A87
  last_name: Henzinger
  orcid: 0000-0002-2985-7724
- first_name: Mathias
  full_name: Lechner, Mathias
  id: 3DC22916-F248-11E8-B48F-1D18A9856A87
  last_name: Lechner
- first_name: Dorde
  full_name: Zikelic, Dorde
  id: 294AA7A6-F248-11E8-B48F-1D18A9856A87
  last_name: Zikelic
  orcid: 0000-0002-4681-1699
citation:
  ama: 'Ansaripour M, Chatterjee K, Henzinger TA, Lechner M, Zikelic D. Learning provably
    stabilizing neural controllers for discrete-time stochastic systems. In: <i>21st
    International Symposium on Automated Technology for Verification and Analysis</i>.
    Vol 14215. Springer Nature; 2023:357-379. doi:<a href="https://doi.org/10.1007/978-3-031-45329-8_17">10.1007/978-3-031-45329-8_17</a>'
  apa: 'Ansaripour, M., Chatterjee, K., Henzinger, T. A., Lechner, M., &#38; Zikelic,
    D. (2023). Learning provably stabilizing neural controllers for discrete-time
    stochastic systems. In <i>21st International Symposium on Automated Technology
    for Verification and Analysis</i> (Vol. 14215, pp. 357–379). Singapore, Singapore:
    Springer Nature. <a href="https://doi.org/10.1007/978-3-031-45329-8_17">https://doi.org/10.1007/978-3-031-45329-8_17</a>'
  chicago: Ansaripour, Matin, Krishnendu Chatterjee, Thomas A Henzinger, Mathias Lechner,
    and Dorde Zikelic. “Learning Provably Stabilizing Neural Controllers for Discrete-Time
    Stochastic Systems.” In <i>21st International Symposium on Automated Technology
    for Verification and Analysis</i>, 14215:357–79. Springer Nature, 2023. <a href="https://doi.org/10.1007/978-3-031-45329-8_17">https://doi.org/10.1007/978-3-031-45329-8_17</a>.
  ieee: M. Ansaripour, K. Chatterjee, T. A. Henzinger, M. Lechner, and D. Zikelic,
    “Learning provably stabilizing neural controllers for discrete-time stochastic
    systems,” in <i>21st International Symposium on Automated Technology for Verification
    and Analysis</i>, Singapore, Singapore, 2023, vol. 14215, pp. 357–379.
  ista: 'Ansaripour M, Chatterjee K, Henzinger TA, Lechner M, Zikelic D. 2023. Learning
    provably stabilizing neural controllers for discrete-time stochastic systems.
    21st International Symposium on Automated Technology for Verification and Analysis.
    ATVA: Automated Technology for Verification and Analysis, LNCS, vol. 14215, 357–379.'
  mla: Ansaripour, Matin, et al. “Learning Provably Stabilizing Neural Controllers
    for Discrete-Time Stochastic Systems.” <i>21st International Symposium on Automated
    Technology for Verification and Analysis</i>, vol. 14215, Springer Nature, 2023,
    pp. 357–79, doi:<a href="https://doi.org/10.1007/978-3-031-45329-8_17">10.1007/978-3-031-45329-8_17</a>.
  short: M. Ansaripour, K. Chatterjee, T.A. Henzinger, M. Lechner, D. Zikelic, in:,
    21st International Symposium on Automated Technology for Verification and Analysis,
    Springer Nature, 2023, pp. 357–379.
conference:
  end_date: 2023-10-27
  location: Singapore, Singapore
  name: 'ATVA: Automated Technology for Verification and Analysis'
  start_date: 2023-10-24
date_created: 2023-11-19T23:00:56Z
date_published: 2023-10-22T00:00:00Z
date_updated: 2025-07-14T09:09:59Z
day: '22'
department:
- _id: ToHe
- _id: KrCh
doi: 10.1007/978-3-031-45329-8_17
ec_funded: 1
intvolume: '     14215'
language:
- iso: eng
month: '10'
oa_version: None
page: 357-379
project:
- _id: 62781420-2b32-11ec-9570-8d9b63373d4d
  call_identifier: H2020
  grant_number: '101020093'
  name: Vigilant Algorithmic Monitoring of Software
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
  call_identifier: H2020
  grant_number: '863818'
  name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
  grant_number: '665385'
  name: International IST Doctoral Program
publication: 21st International Symposium on Automated Technology for Verification
  and Analysis
publication_identifier:
  eissn:
  - 1611-3349
  isbn:
  - '9783031453281'
  issn:
  - 0302-9743
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: Learning provably stabilizing neural controllers for discrete-time stochastic
  systems
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 14215
year: '2023'
...
---
_id: '14591'
abstract:
- lang: eng
  text: Clathrin-mediated endocytosis (CME) is vital for the regulation of plant growth
    and development by controlling plasma membrane protein composition and cargo uptake.
    CME relies on the precise recruitment of regulators for vesicle maturation and
    release. Homologues of components of mammalian vesicle scission are strong candidates
    to be part of the scissin machinery in plants, but the precise roles of these
    proteins in this process is not fully understood. Here, we characterised the roles
    of Plant Dynamin-Related Proteins 2 (DRP2s) and SH3-domain containing protein
    2 (SH3P2), the plant homologue to Dynamins’ recruiters, like Endophilin and Amphiphysin,
    in the CME by combining high-resolution imaging of endocytic events in vivo and
    characterisation of the purified proteins in vitro. Although DRP2s and SH3P2 arrive
    similarly late during CME and physically interact, genetic analysis of the Dsh3p1,2,3
    triple-mutant and complementation assays with non-SH3P2-interacting DRP2 variants
    suggests that SH3P2 does not directly recruit DRP2s to the site of endocytosis.
    These observations imply that despite the presence of many well-conserved endocytic
    components, plants have acquired a distinct mechanism for CME. One Sentence Summary
    In contrast to predictions based on mammalian systems, plant Dynamin-related proteins
    2 are recruited to the site of Clathrin-mediated endocytosis independently of
    BAR-SH3 proteins.
acknowledged_ssus:
- _id: EM-Fac
- _id: LifeSc
- _id: Bio
article_processing_charge: No
author:
- first_name: Nataliia
  full_name: Gnyliukh, Nataliia
  id: 390C1120-F248-11E8-B48F-1D18A9856A87
  last_name: Gnyliukh
  orcid: 0000-0002-2198-0509
- first_name: Alexander J
  full_name: Johnson, Alexander J
  id: 46A62C3A-F248-11E8-B48F-1D18A9856A87
  last_name: Johnson
  orcid: 0000-0002-2739-8843
- first_name: Marie-Kristin
  full_name: Nagel, Marie-Kristin
  last_name: Nagel
- first_name: Aline
  full_name: Monzer, Aline
  id: 2DB5D88C-D7B3-11E9-B8FD-7907E6697425
  last_name: Monzer
- first_name: Annamaria
  full_name: Hlavata, Annamaria
  id: 36062FEC-F248-11E8-B48F-1D18A9856A87
  last_name: Hlavata
- first_name: Erika
  full_name: Isono, Erika
  last_name: Isono
- first_name: Martin
  full_name: Loose, Martin
  id: 462D4284-F248-11E8-B48F-1D18A9856A87
  last_name: Loose
  orcid: 0000-0001-7309-9724
- first_name: Jiří
  full_name: Friml, Jiří
  id: 4159519E-F248-11E8-B48F-1D18A9856A87
  last_name: Friml
  orcid: 0000-0002-8302-7596
citation:
  ama: Gnyliukh N, Johnson AJ, Nagel M-K, et al. Role of dynamin-related proteins
    2 and SH3P2 in clathrin-mediated endocytosis in plants. <i>bioRxiv</i>. doi:<a
    href="https://doi.org/10.1101/2023.10.09.561523">10.1101/2023.10.09.561523</a>
  apa: Gnyliukh, N., Johnson, A. J., Nagel, M.-K., Monzer, A., Hlavata, A., Isono,
    E., … Friml, J. (n.d.). Role of dynamin-related proteins 2 and SH3P2 in clathrin-mediated
    endocytosis in plants. <i>bioRxiv</i>. <a href="https://doi.org/10.1101/2023.10.09.561523">https://doi.org/10.1101/2023.10.09.561523</a>
  chicago: Gnyliukh, Nataliia, Alexander J Johnson, Marie-Kristin Nagel, Aline Monzer,
    Annamaria Hlavata, Erika Isono, Martin Loose, and Jiří Friml. “Role of Dynamin-Related
    Proteins 2 and SH3P2 in Clathrin-Mediated Endocytosis in Plants.” <i>BioRxiv</i>,
    n.d. <a href="https://doi.org/10.1101/2023.10.09.561523">https://doi.org/10.1101/2023.10.09.561523</a>.
  ieee: N. Gnyliukh <i>et al.</i>, “Role of dynamin-related proteins 2 and SH3P2 in
    clathrin-mediated endocytosis in plants,” <i>bioRxiv</i>. .
  ista: Gnyliukh N, Johnson AJ, Nagel M-K, Monzer A, Hlavata A, Isono E, Loose M,
    Friml J. Role of dynamin-related proteins 2 and SH3P2 in clathrin-mediated endocytosis
    in plants. bioRxiv, <a href="https://doi.org/10.1101/2023.10.09.561523">10.1101/2023.10.09.561523</a>.
  mla: Gnyliukh, Nataliia, et al. “Role of Dynamin-Related Proteins 2 and SH3P2 in
    Clathrin-Mediated Endocytosis in Plants.” <i>BioRxiv</i>, doi:<a href="https://doi.org/10.1101/2023.10.09.561523">10.1101/2023.10.09.561523</a>.
  short: N. Gnyliukh, A.J. Johnson, M.-K. Nagel, A. Monzer, A. Hlavata, E. Isono,
    M. Loose, J. Friml, BioRxiv (n.d.).
date_created: 2023-11-22T10:17:49Z
date_published: 2023-10-10T00:00:00Z
date_updated: 2023-12-01T13:51:06Z
day: '10'
department:
- _id: JiFr
- _id: MaLo
- _id: CaBe
doi: 10.1101/2023.10.09.561523
ec_funded: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://www.biorxiv.org/content/10.1101/2023.10.09.561523v2
month: '10'
oa: 1
oa_version: Preprint
project:
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
  grant_number: '665385'
  name: International IST Doctoral Program
publication: bioRxiv
publication_status: submitted
related_material:
  record:
  - id: '14510'
    relation: dissertation_contains
    status: public
status: public
title: Role of dynamin-related proteins 2 and SH3P2 in clathrin-mediated endocytosis
  in plants
type: preprint
user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9
year: '2023'
...
---
_id: '14641'
acknowledged_ssus:
- _id: LifeSc
- _id: Bio
- _id: CampIT
alternative_title:
- ISTA Thesis
article_processing_charge: No
author:
- first_name: Mike
  full_name: Hennessey-Wesen, Mike
  id: 3F338C72-F248-11E8-B48F-1D18A9856A87
  last_name: Hennessey-Wesen
citation:
  ama: Hennessey-Wesen M. Adaptive mutation in E. coli modulated by luxS. 2023. doi:<a
    href="https://doi.org/10.15479/at:ista:14641">10.15479/at:ista:14641</a>
  apa: Hennessey-Wesen, M. (2023). <i>Adaptive mutation in E. coli modulated by luxS</i>.
    Institute of Science and Technology Austria. <a href="https://doi.org/10.15479/at:ista:14641">https://doi.org/10.15479/at:ista:14641</a>
  chicago: Hennessey-Wesen, Mike. “Adaptive Mutation in E. Coli Modulated by LuxS.”
    Institute of Science and Technology Austria, 2023. <a href="https://doi.org/10.15479/at:ista:14641">https://doi.org/10.15479/at:ista:14641</a>.
  ieee: M. Hennessey-Wesen, “Adaptive mutation in E. coli modulated by luxS,” Institute
    of Science and Technology Austria, 2023.
  ista: Hennessey-Wesen M. 2023. Adaptive mutation in E. coli modulated by luxS. Institute
    of Science and Technology Austria.
  mla: Hennessey-Wesen, Mike. <i>Adaptive Mutation in E. Coli Modulated by LuxS</i>.
    Institute of Science and Technology Austria, 2023, doi:<a href="https://doi.org/10.15479/at:ista:14641">10.15479/at:ista:14641</a>.
  short: M. Hennessey-Wesen, Adaptive Mutation in E. Coli Modulated by LuxS, Institute
    of Science and Technology Austria, 2023.
date_created: 2023-12-04T13:17:37Z
date_published: 2023-11-30T00:00:00Z
date_updated: 2023-12-07T14:12:25Z
day: '30'
ddc:
- '570'
degree_awarded: PhD
department:
- _id: GradSch
- _id: BjHo
doi: 10.15479/at:ista:14641
ec_funded: 1
file:
- access_level: closed
  checksum: 4127c285b34f4bf7fb31ef24f9d14c25
  content_type: application/vnd.oasis.opendocument.text
  creator: mhenness
  date_created: 2023-12-06T13:13:26Z
  date_updated: 2023-12-06T13:13:26Z
  file_id: '14648'
  file_name: mike_thesis_v06-12-2023.odt
  file_size: 46405919
  relation: source_file
- access_level: closed
  checksum: f5203a61eddaf35235bbc51904d73982
  content_type: application/pdf
  creator: mhenness
  date_created: 2023-12-06T13:14:15Z
  date_updated: 2023-12-06T13:14:15Z
  embargo: 2024-11-30
  embargo_to: open_access
  file_id: '14649'
  file_name: mike_thesis_v06-12-2023.pdf
  file_size: 21282155
  relation: main_file
file_date_updated: 2023-12-06T13:14:15Z
has_accepted_license: '1'
keyword:
- microfluidics
- miceobiology
- mutations
- quorum sensing
language:
- iso: eng
month: '11'
oa_version: Published Version
page: '104'
project:
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
  grant_number: '665385'
  name: International IST Doctoral Program
publication_identifier:
  issn:
  - 2663 - 337X
publication_status: published
publisher: Institute of Science and Technology Austria
status: public
supervisor:
- first_name: Björn
  full_name: Hof, Björn
  id: 3A374330-F248-11E8-B48F-1D18A9856A87
  last_name: Hof
  orcid: 0000-0003-2057-2754
title: Adaptive mutation in E. coli modulated by luxS
type: dissertation
user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9
year: '2023'
...
---
_id: '14651'
abstract:
- lang: eng
  text: 'For self-incompatibility (SI) to be stable in a population, theory predicts
    that sufficient inbreeding depression (ID) is required: the fitness of offspring
    from self-mated individuals must be low enough to prevent the spread of self-compatibility
    (SC). Reviews of natural plant populations have supported this theory, with SI
    species generally showing high levels of ID. However, there is thought to be an
    under-sampling of self-incompatible taxa in the current literature. In this thesis,
    I study inbreeding depression in the SI plant species Antirrhinum majus using
    both greenhouse crosses and a large collected field dataset. Additionally, the
    gametophytic S-locus of A. majus is highly heterozygous and polymorphic, thus
    making assembly and discovery of S-alleles very difficult. Here, 206 new alleles
    of the male component SLFs are presented, along with a phylogeny showing the high
    conservation with alleles from another Antirrhinum species. Lastly, selected sites
    within the protein structure of SLFs are investigated, with one site in particular
    highlighted as potentially being involved in the SI recognition mechanism.'
acknowledged_ssus:
- _id: ScienComp
alternative_title:
- ISTA Thesis
article_processing_charge: No
author:
- first_name: Louise S
  full_name: Arathoon, Louise S
  id: 2CFCFF98-F248-11E8-B48F-1D18A9856A87
  last_name: Arathoon
  orcid: 0000-0003-1771-714X
citation:
  ama: Arathoon LS. Investigating inbreeding depression and the self-incompatibility
    locus of Antirrhinum majus. 2023. doi:<a href="https://doi.org/10.15479/at:ista:14651">10.15479/at:ista:14651</a>
  apa: Arathoon, L. S. (2023). <i>Investigating inbreeding depression and the self-incompatibility
    locus of Antirrhinum majus</i>. Institute of Science and Technology Austria. <a
    href="https://doi.org/10.15479/at:ista:14651">https://doi.org/10.15479/at:ista:14651</a>
  chicago: Arathoon, Louise S. “Investigating Inbreeding Depression and the Self-Incompatibility
    Locus of Antirrhinum Majus.” Institute of Science and Technology Austria, 2023.
    <a href="https://doi.org/10.15479/at:ista:14651">https://doi.org/10.15479/at:ista:14651</a>.
  ieee: L. S. Arathoon, “Investigating inbreeding depression and the self-incompatibility
    locus of Antirrhinum majus,” Institute of Science and Technology Austria, 2023.
  ista: Arathoon LS. 2023. Investigating inbreeding depression and the self-incompatibility
    locus of Antirrhinum majus. Institute of Science and Technology Austria.
  mla: Arathoon, Louise S. <i>Investigating Inbreeding Depression and the Self-Incompatibility
    Locus of Antirrhinum Majus</i>. Institute of Science and Technology Austria, 2023,
    doi:<a href="https://doi.org/10.15479/at:ista:14651">10.15479/at:ista:14651</a>.
  short: L.S. Arathoon, Investigating Inbreeding Depression and the Self-Incompatibility
    Locus of Antirrhinum Majus, Institute of Science and Technology Austria, 2023.
date_created: 2023-12-11T19:30:37Z
date_published: 2023-12-12T00:00:00Z
date_updated: 2023-12-22T11:04:45Z
day: '12'
ddc:
- '570'
degree_awarded: PhD
department:
- _id: GradSch
- _id: NiBa
doi: 10.15479/at:ista:14651
ec_funded: 1
file:
- access_level: open_access
  checksum: 520bdb61e95e66070e02824947d2c5fa
  content_type: application/pdf
  creator: larathoo
  date_created: 2023-12-13T15:37:55Z
  date_updated: 2023-12-13T15:37:55Z
  file_id: '14684'
  file_name: Phd_Thesis_LA.pdf
  file_size: 34101468
  relation: main_file
  success: 1
- access_level: closed
  checksum: d8e59afd0817c98fba2564a264508e5c
  content_type: application/zip
  creator: larathoo
  date_created: 2023-12-13T15:42:23Z
  date_updated: 2023-12-14T08:58:18Z
  file_id: '14685'
  file_name: Phd_Thesis_LA.zip
  file_size: 31052872
  relation: source_file
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  checksum: 9a778c949932286f4519e1f1fca2820d
  content_type: application/zip
  creator: larathoo
  date_created: 2023-12-11T19:24:59Z
  date_updated: 2023-12-14T08:58:18Z
  file_id: '14681'
  file_name: Supplementary_Materials.zip
  file_size: 10713896
  relation: supplementary_material
file_date_updated: 2023-12-14T08:58:18Z
has_accepted_license: '1'
language:
- iso: eng
month: '12'
oa: 1
oa_version: Published Version
page: '96'
project:
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
  grant_number: '665385'
  name: International IST Doctoral Program
publication_identifier:
  issn:
  - 2663 - 337X
publication_status: published
publisher: Institute of Science and Technology Austria
related_material:
  record:
  - id: '11411'
    relation: part_of_dissertation
    status: public
status: public
supervisor:
- first_name: Nicholas H
  full_name: Barton, Nicholas H
  id: 4880FE40-F248-11E8-B48F-1D18A9856A87
  last_name: Barton
  orcid: 0000-0002-8548-5240
title: Investigating inbreeding depression and the self-incompatibility locus of Antirrhinum
  majus
type: dissertation
user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9
year: '2023'
...
---
_id: '14656'
abstract:
- lang: eng
  text: Although much is known about how single neurons in the hippocampus represent
    an animal's position, how circuit interactions contribute to spatial coding is
    less well understood. Using a novel statistical estimator and theoretical modeling,
    both developed in the framework of maximum entropy models, we reveal highly structured
    CA1 cell-cell interactions in male rats during open field exploration. The statistics
    of these interactions depend on whether the animal is in a familiar or novel environment.
    In both conditions the circuit interactions optimize the encoding of spatial information,
    but for regimes that differ in the informativeness of their spatial inputs. This
    structure facilitates linear decodability, making the information easy to read
    out by downstream circuits. Overall, our findings suggest that the efficient coding
    hypothesis is not only applicable to individual neuron properties in the sensory
    periphery, but also to neural interactions in the central brain.
acknowledgement: M.N. was supported by the European Union Horizon 2020 Grant 665385.
  J.C. was supported by the European Research Council Consolidator Grant 281511. G.T.
  was supported by the Austrian Science Fund (FWF) Grant P34015. C.S. was supported
  by an Institute of Science and Technology fellow award and by the National Science
  Foundation (NSF) Award No. 1922658. We thank Peter Baracskay, Karola Kaefer, and
  Hugo Malagon-Vina for the acquisition of the data. We also thank Federico Stella,
  Wiktor Młynarski, Dori Derdikman, Colin Bredenberg, Roman Huszar, Heloisa Chiossi,
  Lorenzo Posani, and Mohamady El-Gaby for comments on an earlier version of the manuscript.
article_processing_charge: Yes (in subscription journal)
article_type: original
author:
- first_name: Michele
  full_name: Nardin, Michele
  id: 30BD0376-F248-11E8-B48F-1D18A9856A87
  last_name: Nardin
  orcid: 0000-0001-8849-6570
- first_name: Jozsef L
  full_name: Csicsvari, Jozsef L
  id: 3FA14672-F248-11E8-B48F-1D18A9856A87
  last_name: Csicsvari
  orcid: 0000-0002-5193-4036
- first_name: Gašper
  full_name: Tkačik, Gašper
  id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
  last_name: Tkačik
  orcid: 0000-0002-6699-1455
- first_name: Cristina
  full_name: Savin, Cristina
  id: 3933349E-F248-11E8-B48F-1D18A9856A87
  last_name: Savin
citation:
  ama: Nardin M, Csicsvari JL, Tkačik G, Savin C. The structure of hippocampal CA1
    interactions optimizes spatial coding across experience. <i>The Journal of Neuroscience</i>.
    2023;43(48):8140-8156. doi:<a href="https://doi.org/10.1523/JNEUROSCI.0194-23.2023">10.1523/JNEUROSCI.0194-23.2023</a>
  apa: Nardin, M., Csicsvari, J. L., Tkačik, G., &#38; Savin, C. (2023). The structure
    of hippocampal CA1 interactions optimizes spatial coding across experience. <i>The
    Journal of Neuroscience</i>. Society of Neuroscience. <a href="https://doi.org/10.1523/JNEUROSCI.0194-23.2023">https://doi.org/10.1523/JNEUROSCI.0194-23.2023</a>
  chicago: Nardin, Michele, Jozsef L Csicsvari, Gašper Tkačik, and Cristina Savin.
    “The Structure of Hippocampal CA1 Interactions Optimizes Spatial Coding across
    Experience.” <i>The Journal of Neuroscience</i>. Society of Neuroscience, 2023.
    <a href="https://doi.org/10.1523/JNEUROSCI.0194-23.2023">https://doi.org/10.1523/JNEUROSCI.0194-23.2023</a>.
  ieee: M. Nardin, J. L. Csicsvari, G. Tkačik, and C. Savin, “The structure of hippocampal
    CA1 interactions optimizes spatial coding across experience,” <i>The Journal of
    Neuroscience</i>, vol. 43, no. 48. Society of Neuroscience, pp. 8140–8156, 2023.
  ista: Nardin M, Csicsvari JL, Tkačik G, Savin C. 2023. The structure of hippocampal
    CA1 interactions optimizes spatial coding across experience. The Journal of Neuroscience.
    43(48), 8140–8156.
  mla: Nardin, Michele, et al. “The Structure of Hippocampal CA1 Interactions Optimizes
    Spatial Coding across Experience.” <i>The Journal of Neuroscience</i>, vol. 43,
    no. 48, Society of Neuroscience, 2023, pp. 8140–56, doi:<a href="https://doi.org/10.1523/JNEUROSCI.0194-23.2023">10.1523/JNEUROSCI.0194-23.2023</a>.
  short: M. Nardin, J.L. Csicsvari, G. Tkačik, C. Savin, The Journal of Neuroscience
    43 (2023) 8140–8156.
date_created: 2023-12-10T23:00:58Z
date_published: 2023-11-29T00:00:00Z
date_updated: 2023-12-11T11:37:20Z
day: '29'
ddc:
- '570'
department:
- _id: JoCs
- _id: GaTk
doi: 10.1523/JNEUROSCI.0194-23.2023
ec_funded: 1
external_id:
  pmid:
  - '37758476'
file:
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  file_name: 2023_JourNeuroscience_Nardin.pdf
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has_accepted_license: '1'
intvolume: '        43'
issue: '48'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://doi.org/10.1523/JNEUROSCI.0194-23.2023
month: '11'
oa: 1
oa_version: Published Version
page: 8140-8156
pmid: 1
project:
- _id: 257A4776-B435-11E9-9278-68D0E5697425
  call_identifier: FP7
  grant_number: '281511'
  name: Memory-related information processing in neuronal circuits of the hippocampus
    and entorhinal cortex
- _id: 626c45b5-2b32-11ec-9570-e509828c1ba6
  grant_number: P34015
  name: Efficient coding with biophysical realism
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
  grant_number: '665385'
  name: International IST Doctoral Program
publication: The Journal of Neuroscience
publication_identifier:
  eissn:
  - 1529-2401
publication_status: published
publisher: Society of Neuroscience
quality_controlled: '1'
scopus_import: '1'
status: public
title: The structure of hippocampal CA1 interactions optimizes spatial coding across
  experience
tmp:
  image: /images/cc_by.png
  legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
  name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
  short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 43
year: '2023'
...
---
_id: '14697'
acknowledged_ssus:
- _id: LifeSc
- _id: Bio
alternative_title:
- ISTA Thesis
article_processing_charge: No
author:
- first_name: Julian A
  full_name: Stopp, Julian A
  id: 489E3F00-F248-11E8-B48F-1D18A9856A87
  last_name: Stopp
citation:
  ama: 'Stopp JA. Neutrophils on the hunt: Migratory strategies employed by neutrophils
    to fulfill their effector function. 2023. doi:<a href="https://doi.org/10.15479/at:ista:14697">10.15479/at:ista:14697</a>'
  apa: 'Stopp, J. A. (2023). <i>Neutrophils on the hunt: Migratory strategies employed
    by neutrophils to fulfill their effector function</i>. Institute of Science and
    Technology Austria. <a href="https://doi.org/10.15479/at:ista:14697">https://doi.org/10.15479/at:ista:14697</a>'
  chicago: 'Stopp, Julian A. “Neutrophils on the Hunt: Migratory Strategies Employed
    by Neutrophils to Fulfill Their Effector Function.” Institute of Science and Technology
    Austria, 2023. <a href="https://doi.org/10.15479/at:ista:14697">https://doi.org/10.15479/at:ista:14697</a>.'
  ieee: 'J. A. Stopp, “Neutrophils on the hunt: Migratory strategies employed by neutrophils
    to fulfill their effector function,” Institute of Science and Technology Austria,
    2023.'
  ista: 'Stopp JA. 2023. Neutrophils on the hunt: Migratory strategies employed by
    neutrophils to fulfill their effector function. Institute of Science and Technology
    Austria.'
  mla: 'Stopp, Julian A. <i>Neutrophils on the Hunt: Migratory Strategies Employed
    by Neutrophils to Fulfill Their Effector Function</i>. Institute of Science and
    Technology Austria, 2023, doi:<a href="https://doi.org/10.15479/at:ista:14697">10.15479/at:ista:14697</a>.'
  short: 'J.A. Stopp, Neutrophils on the Hunt: Migratory Strategies Employed by Neutrophils
    to Fulfill Their Effector Function, Institute of Science and Technology Austria,
    2023.'
date_created: 2023-12-18T19:14:28Z
date_published: 2023-12-20T00:00:00Z
date_updated: 2023-12-21T14:30:02Z
day: '20'
ddc:
- '570'
degree_awarded: PhD
department:
- _id: GradSch
- _id: MiSi
doi: 10.15479/at:ista:14697
ec_funded: 1
file:
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  date_created: 2023-12-20T09:35:34Z
  date_updated: 2023-12-20T09:35:34Z
  embargo: 2024-12-20
  embargo_to: open_access
  file_id: '14699'
  file_name: Thesis.pdf
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  relation: main_file
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  checksum: e8d26449ac461f5e8478a62c9507506f
  content_type: application/vnd.openxmlformats-officedocument.wordprocessingml.document
  creator: jstopp
  date_created: 2023-12-20T09:35:35Z
  date_updated: 2023-12-20T10:41:42Z
  file_id: '14700'
  file_name: Thesis.docx
  file_size: 69625950
  relation: source_file
file_date_updated: 2023-12-20T10:41:42Z
has_accepted_license: '1'
language:
- iso: eng
month: '12'
oa_version: Published Version
page: '226'
project:
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
  grant_number: '665385'
  name: International IST Doctoral Program
publication_identifier:
  isbn:
  - 978-3-99078-038-1
  issn:
  - 2663 - 337X
publication_status: published
publisher: Institute of Science and Technology Austria
related_material:
  record:
  - id: '6328'
    relation: part_of_dissertation
    status: public
  - id: '7885'
    relation: part_of_dissertation
    status: public
  - id: '12272'
    relation: part_of_dissertation
    status: public
  - id: '14274'
    relation: part_of_dissertation
    status: public
  - id: '14360'
    relation: part_of_dissertation
    status: public
status: public
supervisor:
- first_name: Michael K
  full_name: Sixt, Michael K
  id: 41E9FBEA-F248-11E8-B48F-1D18A9856A87
  last_name: Sixt
  orcid: 0000-0002-6620-9179
title: 'Neutrophils on the hunt: Migratory strategies employed by neutrophils to fulfill
  their effector function'
type: dissertation
user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9
year: '2023'
...
---
_id: '14778'
abstract:
- lang: eng
  text: 'We consider the almost-sure (a.s.) termination problem for probabilistic
    programs, which are a stochastic extension of classical imperative programs. Lexicographic
    ranking functions provide a sound and practical approach for termination of non-probabilistic
    programs, and their extension to probabilistic programs is achieved via lexicographic
    ranking supermartingales (LexRSMs). However, LexRSMs introduced in the previous
    work have a limitation that impedes their automation: all of their components
    have to be non-negative in all reachable states. This might result in a LexRSM
    not existing even for simple terminating programs. Our contributions are twofold.
    First, we introduce a generalization of LexRSMs that allows for some components
    to be negative. This standard feature of non-probabilistic termination proofs
    was hitherto not known to be sound in the probabilistic setting, as the soundness
    proof requires a careful analysis of the underlying stochastic process. Second,
    we present polynomial-time algorithms using our generalized LexRSMs for proving
    a.s. termination in broad classes of linear-arithmetic programs.'
acknowledgement: This research was partially supported by the ERC CoG (grant no. 863818;
  ForM-SMArt), the Czech Science Foundation (grant no. GA21-24711S), and the European
  Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie
  Grant Agreement No. 665385.
article_number: '11'
article_processing_charge: Yes (via OA deal)
article_type: original
arxiv: 1
author:
- first_name: Krishnendu
  full_name: Chatterjee, Krishnendu
  id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
  last_name: Chatterjee
  orcid: 0000-0002-4561-241X
- first_name: Ehsan
  full_name: Kafshdar Goharshady, Ehsan
  last_name: Kafshdar Goharshady
- first_name: Petr
  full_name: Novotný, Petr
  id: 3CC3B868-F248-11E8-B48F-1D18A9856A87
  last_name: Novotný
- first_name: Jiří
  full_name: Zárevúcky, Jiří
  last_name: Zárevúcky
- first_name: Dorde
  full_name: Zikelic, Dorde
  id: 294AA7A6-F248-11E8-B48F-1D18A9856A87
  last_name: Zikelic
  orcid: 0000-0002-4681-1699
citation:
  ama: Chatterjee K, Kafshdar Goharshady E, Novotný P, Zárevúcky J, Zikelic D. On
    lexicographic proof rules for probabilistic termination. <i>Formal Aspects of
    Computing</i>. 2023;35(2). doi:<a href="https://doi.org/10.1145/3585391">10.1145/3585391</a>
  apa: Chatterjee, K., Kafshdar Goharshady, E., Novotný, P., Zárevúcky, J., &#38;
    Zikelic, D. (2023). On lexicographic proof rules for probabilistic termination.
    <i>Formal Aspects of Computing</i>. Association for Computing Machinery. <a href="https://doi.org/10.1145/3585391">https://doi.org/10.1145/3585391</a>
  chicago: Chatterjee, Krishnendu, Ehsan Kafshdar Goharshady, Petr Novotný, Jiří Zárevúcky,
    and Dorde Zikelic. “On Lexicographic Proof Rules for Probabilistic Termination.”
    <i>Formal Aspects of Computing</i>. Association for Computing Machinery, 2023.
    <a href="https://doi.org/10.1145/3585391">https://doi.org/10.1145/3585391</a>.
  ieee: K. Chatterjee, E. Kafshdar Goharshady, P. Novotný, J. Zárevúcky, and D. Zikelic,
    “On lexicographic proof rules for probabilistic termination,” <i>Formal Aspects
    of Computing</i>, vol. 35, no. 2. Association for Computing Machinery, 2023.
  ista: Chatterjee K, Kafshdar Goharshady E, Novotný P, Zárevúcky J, Zikelic D. 2023.
    On lexicographic proof rules for probabilistic termination. Formal Aspects of
    Computing. 35(2), 11.
  mla: Chatterjee, Krishnendu, et al. “On Lexicographic Proof Rules for Probabilistic
    Termination.” <i>Formal Aspects of Computing</i>, vol. 35, no. 2, 11, Association
    for Computing Machinery, 2023, doi:<a href="https://doi.org/10.1145/3585391">10.1145/3585391</a>.
  short: K. Chatterjee, E. Kafshdar Goharshady, P. Novotný, J. Zárevúcky, D. Zikelic,
    Formal Aspects of Computing 35 (2023).
date_created: 2024-01-10T09:27:43Z
date_published: 2023-06-23T00:00:00Z
date_updated: 2025-07-14T09:10:10Z
day: '23'
ddc:
- '000'
department:
- _id: KrCh
doi: 10.1145/3585391
ec_funded: 1
external_id:
  arxiv:
  - '2108.02188'
file:
- access_level: open_access
  checksum: 3bb133eeb27ec01649a9a36445d952d9
  content_type: application/pdf
  creator: dernst
  date_created: 2024-01-16T08:11:24Z
  date_updated: 2024-01-16T08:11:24Z
  file_id: '14804'
  file_name: 2023_FormalAspectsComputing_Chatterjee.pdf
  file_size: 502522
  relation: main_file
  success: 1
file_date_updated: 2024-01-16T08:11:24Z
has_accepted_license: '1'
intvolume: '        35'
issue: '2'
keyword:
- Theoretical Computer Science
- Software
language:
- iso: eng
month: '06'
oa: 1
oa_version: Published Version
project:
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
  call_identifier: H2020
  grant_number: '863818'
  name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
  grant_number: '665385'
  name: International IST Doctoral Program
publication: Formal Aspects of Computing
publication_identifier:
  eissn:
  - 1433-299X
  issn:
  - 0934-5043
publication_status: published
publisher: Association for Computing Machinery
quality_controlled: '1'
related_material:
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    relation: earlier_version
    status: public
status: public
title: On lexicographic proof rules for probabilistic termination
tmp:
  image: /images/cc_by.png
  legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
  name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
  short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 35
year: '2023'
...
---
_id: '14830'
abstract:
- lang: eng
  text: We study the problem of learning controllers for discrete-time non-linear
    stochastic dynamical systems with formal reach-avoid guarantees. This work presents
    the first method for providing formal reach-avoid guarantees, which combine and
    generalize stability and safety guarantees, with a tolerable probability threshold
    p in [0,1] over the infinite time horizon. Our method leverages advances in machine
    learning literature and it represents formal certificates as neural networks.
    In particular, we learn a certificate in the form of a reach-avoid supermartingale
    (RASM), a novel notion that we introduce in this work. Our RASMs provide reachability
    and avoidance guarantees by imposing constraints on what can be viewed as a stochastic
    extension of level sets of Lyapunov functions for deterministic systems. Our approach
    solves several important problems -- it can be used to learn a control policy
    from scratch, to verify a reach-avoid specification for a fixed control policy,
    or to fine-tune a pre-trained policy if it does not satisfy the reach-avoid specification.
    We validate our approach on 3 stochastic non-linear reinforcement learning tasks.
acknowledgement: This work was supported in part by the ERC-2020-AdG 101020093, ERC
  CoG 863818 (FoRM-SMArt) and the European Union’s Horizon 2020 research and innovation
  programme under the Marie Skłodowska-Curie Grant Agreement No. 665385.
article_processing_charge: No
arxiv: 1
author:
- first_name: Dorde
  full_name: Zikelic, Dorde
  id: 294AA7A6-F248-11E8-B48F-1D18A9856A87
  last_name: Zikelic
  orcid: 0000-0002-4681-1699
- first_name: Mathias
  full_name: Lechner, Mathias
  id: 3DC22916-F248-11E8-B48F-1D18A9856A87
  last_name: Lechner
- first_name: Thomas A
  full_name: Henzinger, Thomas A
  id: 40876CD8-F248-11E8-B48F-1D18A9856A87
  last_name: Henzinger
  orcid: 0000-0002-2985-7724
- first_name: Krishnendu
  full_name: Chatterjee, Krishnendu
  id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
  last_name: Chatterjee
  orcid: 0000-0002-4561-241X
citation:
  ama: 'Zikelic D, Lechner M, Henzinger TA, Chatterjee K. Learning control policies
    for stochastic systems with reach-avoid guarantees. In: <i>Proceedings of the
    37th AAAI Conference on Artificial Intelligence</i>. Vol 37. Association for the
    Advancement of Artificial Intelligence; 2023:11926-11935. doi:<a href="https://doi.org/10.1609/aaai.v37i10.26407">10.1609/aaai.v37i10.26407</a>'
  apa: 'Zikelic, D., Lechner, M., Henzinger, T. A., &#38; Chatterjee, K. (2023). Learning
    control policies for stochastic systems with reach-avoid guarantees. In <i>Proceedings
    of the 37th AAAI Conference on Artificial Intelligence</i> (Vol. 37, pp. 11926–11935).
    Washington, DC, United States: Association for the Advancement of Artificial Intelligence.
    <a href="https://doi.org/10.1609/aaai.v37i10.26407">https://doi.org/10.1609/aaai.v37i10.26407</a>'
  chicago: Zikelic, Dorde, Mathias Lechner, Thomas A Henzinger, and Krishnendu Chatterjee.
    “Learning Control Policies for Stochastic Systems with Reach-Avoid Guarantees.”
    In <i>Proceedings of the 37th AAAI Conference on Artificial Intelligence</i>,
    37:11926–35. Association for the Advancement of Artificial Intelligence, 2023.
    <a href="https://doi.org/10.1609/aaai.v37i10.26407">https://doi.org/10.1609/aaai.v37i10.26407</a>.
  ieee: D. Zikelic, M. Lechner, T. A. Henzinger, and K. Chatterjee, “Learning control
    policies for stochastic systems with reach-avoid guarantees,” in <i>Proceedings
    of the 37th AAAI Conference on Artificial Intelligence</i>, Washington, DC, United
    States, 2023, vol. 37, no. 10, pp. 11926–11935.
  ista: 'Zikelic D, Lechner M, Henzinger TA, Chatterjee K. 2023. Learning control
    policies for stochastic systems with reach-avoid guarantees. Proceedings of the
    37th AAAI Conference on Artificial Intelligence. AAAI: Conference on Artificial
    Intelligence vol. 37, 11926–11935.'
  mla: Zikelic, Dorde, et al. “Learning Control Policies for Stochastic Systems with
    Reach-Avoid Guarantees.” <i>Proceedings of the 37th AAAI Conference on Artificial
    Intelligence</i>, vol. 37, no. 10, Association for the Advancement of Artificial
    Intelligence, 2023, pp. 11926–35, doi:<a href="https://doi.org/10.1609/aaai.v37i10.26407">10.1609/aaai.v37i10.26407</a>.
  short: D. Zikelic, M. Lechner, T.A. Henzinger, K. Chatterjee, in:, Proceedings of
    the 37th AAAI Conference on Artificial Intelligence, Association for the Advancement
    of Artificial Intelligence, 2023, pp. 11926–11935.
conference:
  end_date: 2023-02-14
  location: Washington, DC, United States
  name: 'AAAI: Conference on Artificial Intelligence'
  start_date: 2023-02-07
date_created: 2024-01-18T07:44:31Z
date_published: 2023-06-26T00:00:00Z
date_updated: 2025-07-14T09:10:02Z
day: '26'
department:
- _id: ToHe
- _id: KrCh
doi: 10.1609/aaai.v37i10.26407
ec_funded: 1
external_id:
  arxiv:
  - '2210.05308'
intvolume: '        37'
issue: '10'
keyword:
- General Medicine
language:
- iso: eng
month: '06'
oa_version: Preprint
page: 11926-11935
project:
- _id: 62781420-2b32-11ec-9570-8d9b63373d4d
  call_identifier: H2020
  grant_number: '101020093'
  name: Vigilant Algorithmic Monitoring of Software
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
  call_identifier: H2020
  grant_number: '863818'
  name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
  grant_number: '665385'
  name: International IST Doctoral Program
publication: Proceedings of the 37th AAAI Conference on Artificial Intelligence
publication_identifier:
  eissn:
  - 2374-3468
  issn:
  - 2159-5399
publication_status: published
publisher: Association for the Advancement of Artificial Intelligence
quality_controlled: '1'
related_material:
  record:
  - id: '14600'
    relation: earlier_version
    status: public
status: public
title: Learning control policies for stochastic systems with reach-avoid guarantees
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 37
year: '2023'
...
---
_id: '13074'
abstract:
- lang: eng
  text: "Deep learning has become an integral part of a large number of important
    applications, and many of the recent breakthroughs have been enabled by the ability
    to train very large models, capable to capture complex patterns and relationships
    from the data. At the same time, the massive sizes of modern deep learning models
    have made their deployment to smaller devices more challenging; this is particularly
    important, as in many applications the users rely on accurate deep learning predictions,
    but they only have access to devices with limited memory and compute power. One
    solution to this problem is to prune neural networks, by setting as many of their
    parameters as possible to zero, to obtain accurate sparse models with lower memory
    footprint. Despite the great research progress in obtaining sparse models that
    preserve accuracy, while satisfying memory and computational constraints, there
    are still many challenges associated with efficiently training sparse models,
    as well as understanding their generalization properties.\r\n\r\nThe focus of
    this thesis is to investigate how the training process of sparse models can be
    made more efficient, and to understand the differences between sparse and dense
    models in terms of how well they can generalize to changes in the data distribution.
    We first study a method for co-training sparse and dense models, at a lower cost
    compared to regular training. With our method we can obtain very accurate sparse
    networks, and dense models that can recover the baseline accuracy. Furthermore,
    we are able to more easily analyze the differences, at prediction level, between
    the sparse-dense model pairs. Next, we investigate the generalization properties
    of sparse neural networks in more detail, by studying how well different sparse
    models trained on a larger task can adapt to smaller, more specialized tasks,
    in a transfer learning scenario. Our analysis across multiple pruning methods
    and sparsity levels reveals that sparse models provide features that can transfer
    similarly to or better than the dense baseline. However, the choice of the pruning
    method plays an important role, and can influence the results when the features
    are fixed (linear finetuning), or when they are allowed to adapt to the new task
    (full finetuning). Using sparse models with fixed masks for finetuning on new
    tasks has an important practical advantage, as it enables training neural networks
    on smaller devices. However, one drawback of current pruning methods is that the
    entire training cycle has to be repeated to obtain the initial sparse model, for
    every sparsity target; in consequence, the entire training process is costly and
    also multiple models need to be stored. In the last part of the thesis we propose
    a method that can train accurate dense models that are compressible in a single
    step, to multiple sparsity levels, without additional finetuning. Our method results
    in sparse models that can be competitive with existing pruning methods, and which
    can also successfully generalize to new tasks."
acknowledged_ssus:
- _id: ScienComp
alternative_title:
- ISTA Thesis
article_processing_charge: No
author:
- first_name: Elena-Alexandra
  full_name: Peste, Elena-Alexandra
  id: 32D78294-F248-11E8-B48F-1D18A9856A87
  last_name: Peste
citation:
  ama: Peste E-A. Efficiency and generalization of sparse neural networks. 2023. doi:<a
    href="https://doi.org/10.15479/at:ista:13074">10.15479/at:ista:13074</a>
  apa: Peste, E.-A. (2023). <i>Efficiency and generalization of sparse neural networks</i>.
    Institute of Science and Technology Austria. <a href="https://doi.org/10.15479/at:ista:13074">https://doi.org/10.15479/at:ista:13074</a>
  chicago: Peste, Elena-Alexandra. “Efficiency and Generalization of Sparse Neural
    Networks.” Institute of Science and Technology Austria, 2023. <a href="https://doi.org/10.15479/at:ista:13074">https://doi.org/10.15479/at:ista:13074</a>.
  ieee: E.-A. Peste, “Efficiency and generalization of sparse neural networks,” Institute
    of Science and Technology Austria, 2023.
  ista: Peste E-A. 2023. Efficiency and generalization of sparse neural networks.
    Institute of Science and Technology Austria.
  mla: Peste, Elena-Alexandra. <i>Efficiency and Generalization of Sparse Neural Networks</i>.
    Institute of Science and Technology Austria, 2023, doi:<a href="https://doi.org/10.15479/at:ista:13074">10.15479/at:ista:13074</a>.
  short: E.-A. Peste, Efficiency and Generalization of Sparse Neural Networks, Institute
    of Science and Technology Austria, 2023.
date_created: 2023-05-23T17:07:53Z
date_published: 2023-05-23T00:00:00Z
date_updated: 2023-08-04T10:33:27Z
day: '23'
ddc:
- '000'
degree_awarded: PhD
department:
- _id: GradSch
- _id: DaAl
- _id: ChLa
doi: 10.15479/at:ista:13074
ec_funded: 1
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has_accepted_license: '1'
language:
- iso: eng
month: '05'
oa: 1
oa_version: Published Version
page: '147'
project:
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
  grant_number: '665385'
  name: International IST Doctoral Program
- _id: 268A44D6-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
  grant_number: '805223'
  name: Elastic Coordination for Scalable Machine Learning
publication_identifier:
  issn:
  - 2663-337X
publication_status: published
publisher: Institute of Science and Technology Austria
related_material:
  record:
  - id: '11458'
    relation: part_of_dissertation
    status: public
  - id: '13053'
    relation: part_of_dissertation
    status: public
  - id: '12299'
    relation: part_of_dissertation
    status: public
status: public
supervisor:
- first_name: Christoph
  full_name: Lampert, Christoph
  id: 40C20FD2-F248-11E8-B48F-1D18A9856A87
  last_name: Lampert
  orcid: 0000-0001-8622-7887
- first_name: Dan-Adrian
  full_name: Alistarh, Dan-Adrian
  id: 4A899BFC-F248-11E8-B48F-1D18A9856A87
  last_name: Alistarh
  orcid: 0000-0003-3650-940X
title: Efficiency and generalization of sparse neural networks
type: dissertation
user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9
year: '2023'
...
---
_id: '13126'
abstract:
- lang: eng
  text: Mapping the complex and dense arrangement of cells and their connectivity
    in brain tissue demands nanoscale spatial resolution imaging. Super-resolution
    optical microscopy excels at visualizing specific molecules and individual cells
    but fails to provide tissue context. Here, we developed Comprehensive Analysis
    of Tissues across Scales (CATS), a technology to densely map brain tissue architecture
    from millimeter regional to nanometer synaptic scales in diverse chemically fixed
    brain preparations, including rodent and human. CATS uses fixation-compatible
    extracellular labeling and optical imaging, including stimulated emission depletion
    or expansion microscopy, to comprehensively delineate cellular structures. It
    enables three-dimensional reconstruction of single synapses and mapping of synaptic
    connectivity by identification and analysis of putative synaptic cleft regions.
    Applying CATS to the mouse hippocampal mossy fiber circuitry, we reconstructed
    and quantified the synaptic input and output structure of identified neurons.
    We furthermore demonstrate applicability to clinically derived human tissue samples,
    including formalin-fixed paraffin-embedded routine diagnostic specimens, for visualizing
    the cellular architecture of brain tissue in health and disease.
acknowledged_ssus:
- _id: ScienComp
- _id: Bio
- _id: PreCl
- _id: LifeSc
- _id: M-Shop
- _id: E-Lib
acknowledgement: "We thank Jakob Vorlaufer, Nathalie Agudelo-Dueñas, Wiebke Jahr,
  Andreas Wartak for microscope maintenance and troubleshooting, Caroline Kreuzinger,
  Anna Freeman, and Irene Erber for technical assistance and Matthias Tomschik for
  support with obtaining human samples. We gratefully acknowledge Eder Miguel for
  setting up webKnossos and Marek Šuplata for computational support and hardware control.
  We are grateful to Ryuichi Shigemoto and Bernd Bickel for generous support, and
  Michael Sixt and Scott Boyd (Stanford University) for discussions and critical reading
  of the manuscript. PSD95-HaloTag mice were kindly provided by Seth Grant (University
  of Edinburgh). We acknowledge expert support by IST Austria’s scientific computing,
  imaging and optics, preclinical, and lab support facilities, and by the Library
  and Miba machine shop.\r\nWe gratefully acknowledge funding by the following sources:
  \r\nAustrian Science Fund (FWF) grant I3600-B27 (JGD)\r\nAustrian Science Fund (FWF)
  grant DK W1232 (JGD, JMM)\r\nAustrian Science Fund (FWF) grant Z 312-B27, Wittgenstein
  award (PJ)\r\nAustrian Science Funds (FWF) projects I4685-B, I6565-B (SYNABS) and
  DOC 33-B27 (RH)\r\nGesellschaft für Forschungsförderung NÖ (NFB) grant LSC18-022
  (JGD)\r\nEuropean Union’s Horizon 2020 research and innovation programme, European
  Research Council (ERC) grant 715508 – REVERSEAUTISM (GN)\r\nEuropean Union’s Horizon
  2020 research and innovation programme, European Research Council (ERC) grant 692692
  – GIANTSYN (PJ)\r\nMarie Skłodowska-Curie Actions Fellowship GA no. 665385 under
  the EU Horizon 2020 program (JMM, JL)\r\nMarie Skłodowska-Curie Actions Individual
  Fellowship 101026635 under the EU Horizon 2020 program (JFW)"
article_processing_charge: No
author:
- first_name: Johann G
  full_name: Danzl, Johann G
  id: 42EFD3B6-F248-11E8-B48F-1D18A9856A87
  last_name: Danzl
  orcid: 0000-0001-8559-3973
citation:
  ama: Danzl JG. Research data for the publication “Imaging brain tissue architecture
    across millimeter to nanometer scales.” 2023. doi:<a href="https://doi.org/10.15479/AT:ISTA:13126">10.15479/AT:ISTA:13126</a>
  apa: Danzl, J. G. (2023). Research data for the publication “Imaging brain tissue
    architecture across millimeter to nanometer scales.” Institute of Science and
    Technology Austria. <a href="https://doi.org/10.15479/AT:ISTA:13126">https://doi.org/10.15479/AT:ISTA:13126</a>
  chicago: Danzl, Johann G. “Research Data for the Publication ‘Imaging Brain Tissue
    Architecture across Millimeter to Nanometer Scales.’” Institute of Science and
    Technology Austria, 2023. <a href="https://doi.org/10.15479/AT:ISTA:13126">https://doi.org/10.15479/AT:ISTA:13126</a>.
  ieee: J. G. Danzl, “Research data for the publication ‘Imaging brain tissue architecture
    across millimeter to nanometer scales.’” Institute of Science and Technology Austria,
    2023.
  ista: Danzl JG. 2023. Research data for the publication ‘Imaging brain tissue architecture
    across millimeter to nanometer scales’, Institute of Science and Technology Austria,
    <a href="https://doi.org/10.15479/AT:ISTA:13126">10.15479/AT:ISTA:13126</a>.
  mla: Danzl, Johann G. <i>Research Data for the Publication “Imaging Brain Tissue
    Architecture across Millimeter to Nanometer Scales.”</i> Institute of Science
    and Technology Austria, 2023, doi:<a href="https://doi.org/10.15479/AT:ISTA:13126">10.15479/AT:ISTA:13126</a>.
  short: J.G. Danzl, (2023).
contributor:
- first_name: Julia M
  id: 443DB6DE-F248-11E8-B48F-1D18A9856A87
  last_name: Michalska
- first_name: Julia
  id: 46E28B80-F248-11E8-B48F-1D18A9856A87
  last_name: Lyudchik
- first_name: Philipp
  id: 39BDC62C-F248-11E8-B48F-1D18A9856A87
  last_name: Velicky
  orcid: 0000-0002-2340-7431
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  id: ee3cb6ca-ec98-11ea-ae11-ff703e2254ed
  last_name: Stefanickova
- first_name: Jake
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  last_name: Watson
  orcid: 0000-0002-8698-3823
- first_name: Alban
  id: 9ac8f577-2357-11eb-997a-e566c5550886
  last_name: Cenameri
- first_name: Christoph M
  id: 4DF26D8C-F248-11E8-B48F-1D18A9856A87
  last_name: Sommer
  orcid: 0000-0003-1216-9105
- first_name: Nicole
  id: 4CD6AAC6-F248-11E8-B48F-1D18A9856A87
  last_name: Amberg
  orcid: 0000-0002-3183-8207
- first_name: Alessandro
  id: 41CB84B2-F248-11E8-B48F-1D18A9856A87
  last_name: Venturino
  orcid: 0000-0003-2356-9403
- first_name: Karl
  last_name: Roessler
- first_name: Thomas
  last_name: Czech
- first_name: Romana
  last_name: Höftberger
- first_name: Sandra
  id: 36ACD32E-F248-11E8-B48F-1D18A9856A87
  last_name: Siegert
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  id: 3E57A680-F248-11E8-B48F-1D18A9856A87
  last_name: Novarino
  orcid: 0000-0002-7673-7178
- first_name: Peter M
  id: 353C1B58-F248-11E8-B48F-1D18A9856A87
  last_name: Jonas
  orcid: 0000-0001-5001-4804
date_created: 2023-06-07T07:15:12Z
date_published: 2023-08-04T00:00:00Z
date_updated: 2024-02-21T12:18:19Z
day: '04'
ddc:
- '610'
department:
- _id: JoDa
- _id: SaSi
- _id: GaNo
- _id: PeJo
- _id: Bio
- _id: RySh
doi: 10.15479/AT:ISTA:13126
ec_funded: 1
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- _id: 25C5A090-B435-11E9-9278-68D0E5697425
  call_identifier: FWF
  grant_number: Z00312
  name: The Wittgenstein Prize
- _id: 23889792-32DE-11EA-91FC-C7463DDC885E
  name: High content imaging to decode human immune cell interactions in health and
    allergic disease
- _id: 25444568-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
  grant_number: '715508'
  name: Probing the Reversibility of Autism Spectrum Disorders by Employing in vivo
    and in vitro Models
- _id: 25B7EB9E-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
  grant_number: '692692'
  name: Biophysics and circuit function of a giant cortical glumatergic synapse
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
  grant_number: '665385'
  name: International IST Doctoral Program
- _id: fc2be41b-9c52-11eb-aca3-faa90aa144e9
  call_identifier: H2020
  grant_number: '101026635'
  name: Synaptic computations of the hippocampal CA3 circuitry
publisher: Institute of Science and Technology Austria
related_material:
  link:
  - description: 'Original data for Fig. 5d, Fig. 5d (N2V) and Fig. 5f-i, provided
      via an external link due to the large size (>10GB) of the datasets. '
    relation: research_data
    url: https://pub.ista.ac.at/group_danzl/data/CATS/
  record:
  - id: '14257'
    relation: used_in_publication
    status: public
status: public
title: Research data for the publication "Imaging brain tissue architecture across
  millimeter to nanometer scales"
tmp:
  image: /images/cc_by_nc_sa.png
  legal_code_url: https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode
  name: Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC
    BY-NC-SA 4.0)
  short: CC BY-NC-SA (4.0)
type: research_data
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2023'
...
---
_id: '13142'
abstract:
- lang: eng
  text: Reinforcement learning has received much attention for learning controllers
    of deterministic systems. We consider a learner-verifier framework for stochastic
    control systems and survey recent methods that formally guarantee a conjunction
    of reachability and safety properties. Given a property and a lower bound on the
    probability of the property being satisfied, our framework jointly learns a control
    policy and a formal certificate to ensure the satisfaction of the property with
    a desired probability threshold. Both the control policy and the formal certificate
    are continuous functions from states to reals, which are learned as parameterized
    neural networks. While in the deterministic case, the certificates are invariant
    and barrier functions for safety, or Lyapunov and ranking functions for liveness,
    in the stochastic case the certificates are supermartingales. For certificate
    verification, we use interval arithmetic abstract interpretation to bound the
    expected values of neural network functions.
acknowledgement: This work was supported in part by the ERC-2020-AdG 101020093, ERC
  CoG 863818 (FoRM-SMArt) and the European Union’s Horizon 2020 research and innovation
  programme under the Marie Skłodowska-Curie Grant Agreement No. 665385.
alternative_title:
- LNCS
article_processing_charge: No
author:
- first_name: Krishnendu
  full_name: Chatterjee, Krishnendu
  id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
  last_name: Chatterjee
  orcid: 0000-0002-4561-241X
- first_name: Thomas A
  full_name: Henzinger, Thomas A
  id: 40876CD8-F248-11E8-B48F-1D18A9856A87
  last_name: Henzinger
  orcid: 0000-0002-2985-7724
- first_name: Mathias
  full_name: Lechner, Mathias
  id: 3DC22916-F248-11E8-B48F-1D18A9856A87
  last_name: Lechner
- first_name: Dorde
  full_name: Zikelic, Dorde
  id: 294AA7A6-F248-11E8-B48F-1D18A9856A87
  last_name: Zikelic
  orcid: 0000-0002-4681-1699
citation:
  ama: 'Chatterjee K, Henzinger TA, Lechner M, Zikelic D. A learner-verifier framework
    for neural network controllers and certificates of stochastic systems. In: <i>Tools
    and Algorithms for the Construction and Analysis of Systems </i>. Vol 13993. Springer
    Nature; 2023:3-25. doi:<a href="https://doi.org/10.1007/978-3-031-30823-9_1">10.1007/978-3-031-30823-9_1</a>'
  apa: 'Chatterjee, K., Henzinger, T. A., Lechner, M., &#38; Zikelic, D. (2023). A
    learner-verifier framework for neural network controllers and certificates of
    stochastic systems. In <i>Tools and Algorithms for the Construction and Analysis
    of Systems </i> (Vol. 13993, pp. 3–25). Paris, France: Springer Nature. <a href="https://doi.org/10.1007/978-3-031-30823-9_1">https://doi.org/10.1007/978-3-031-30823-9_1</a>'
  chicago: Chatterjee, Krishnendu, Thomas A Henzinger, Mathias Lechner, and Dorde
    Zikelic. “A Learner-Verifier Framework for Neural Network Controllers and Certificates
    of Stochastic Systems.” In <i>Tools and Algorithms for the Construction and Analysis
    of Systems </i>, 13993:3–25. Springer Nature, 2023. <a href="https://doi.org/10.1007/978-3-031-30823-9_1">https://doi.org/10.1007/978-3-031-30823-9_1</a>.
  ieee: K. Chatterjee, T. A. Henzinger, M. Lechner, and D. Zikelic, “A learner-verifier
    framework for neural network controllers and certificates of stochastic systems,”
    in <i>Tools and Algorithms for the Construction and Analysis of Systems </i>,
    Paris, France, 2023, vol. 13993, pp. 3–25.
  ista: 'Chatterjee K, Henzinger TA, Lechner M, Zikelic D. 2023. A learner-verifier
    framework for neural network controllers and certificates of stochastic systems.
    Tools and Algorithms for the Construction and Analysis of Systems . TACAS: Tools
    and Algorithms for the Construction and Analysis of Systems, LNCS, vol. 13993,
    3–25.'
  mla: Chatterjee, Krishnendu, et al. “A Learner-Verifier Framework for Neural Network
    Controllers and Certificates of Stochastic Systems.” <i>Tools and Algorithms for
    the Construction and Analysis of Systems </i>, vol. 13993, Springer Nature, 2023,
    pp. 3–25, doi:<a href="https://doi.org/10.1007/978-3-031-30823-9_1">10.1007/978-3-031-30823-9_1</a>.
  short: K. Chatterjee, T.A. Henzinger, M. Lechner, D. Zikelic, in:, Tools and Algorithms
    for the Construction and Analysis of Systems , Springer Nature, 2023, pp. 3–25.
conference:
  end_date: 2023-04-27
  location: Paris, France
  name: 'TACAS: Tools and Algorithms for the Construction and Analysis of Systems'
  start_date: 2023-04-22
date_created: 2023-06-18T22:00:47Z
date_published: 2023-04-22T00:00:00Z
date_updated: 2025-07-14T09:09:52Z
day: '22'
ddc:
- '000'
department:
- _id: KrCh
- _id: ToHe
doi: 10.1007/978-3-031-30823-9_1
ec_funded: 1
file:
- access_level: open_access
  checksum: 3d8a8bb24d211bc83360dfc2fd744307
  content_type: application/pdf
  creator: dernst
  date_created: 2023-06-19T08:29:30Z
  date_updated: 2023-06-19T08:29:30Z
  file_id: '13150'
  file_name: 2023_LNCS_Chatterjee.pdf
  file_size: 528455
  relation: main_file
  success: 1
file_date_updated: 2023-06-19T08:29:30Z
has_accepted_license: '1'
intvolume: '     13993'
language:
- iso: eng
month: '04'
oa: 1
oa_version: Published Version
page: 3-25
project:
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
  call_identifier: H2020
  grant_number: '863818'
  name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
  grant_number: '665385'
  name: International IST Doctoral Program
publication: 'Tools and Algorithms for the Construction and Analysis of Systems '
publication_identifier:
  eissn:
  - 1611-3349
  isbn:
  - '9783031308222'
  issn:
  - 0302-9743
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: A learner-verifier framework for neural network controllers and certificates
  of stochastic systems
tmp:
  image: /images/cc_by.png
  legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
  name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
  short: CC BY (4.0)
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 13993
year: '2023'
...
---
_id: '13267'
abstract:
- lang: eng
  text: Three-dimensional (3D) reconstruction of living brain tissue down to an individual
    synapse level would create opportunities for decoding the dynamics and structure–function
    relationships of the brain’s complex and dense information processing network;
    however, this has been hindered by insufficient 3D resolution, inadequate signal-to-noise
    ratio and prohibitive light burden in optical imaging, whereas electron microscopy
    is inherently static. Here we solved these challenges by developing an integrated
    optical/machine-learning technology, LIONESS (live information-optimized nanoscopy
    enabling saturated segmentation). This leverages optical modifications to stimulated
    emission depletion microscopy in comprehensively, extracellularly labeled tissue
    and previous information on sample structure via machine learning to simultaneously
    achieve isotropic super-resolution, high signal-to-noise ratio and compatibility
    with living tissue. This allows dense deep-learning-based instance segmentation
    and 3D reconstruction at a synapse level, incorporating molecular, activity and
    morphodynamic information. LIONESS opens up avenues for studying the dynamic functional
    (nano-)architecture of living brain tissue.
acknowledged_ssus:
- _id: ScienComp
- _id: Bio
- _id: PreCl
- _id: E-Lib
- _id: LifeSc
- _id: M-Shop
acknowledgement: "We thank J. Vorlaufer, N. Agudelo and A. Wartak for microscope maintenance
  and troubleshooting, C. Kreuzinger and A. Freeman for technical assistance, M. Šuplata
  for hardware control support and M. Cunha dos Santos for initial exploration of
  software. We\r\nthank P. Henderson for advice on deep-learning training and M. Sixt,
  S. Boyd and T. Weiss for discussions and critical reading of the manuscript. L.
  Lavis (Janelia Research Campus) generously provided the JF585-HaloTag ligand. We
  acknowledge expert support by IST\r\nAustria’s scientific computing, imaging and
  optics, preclinical, library and laboratory support facilities and by the Miba machine
  shop. We gratefully acknowledge funding by the following sources: Austrian Science
  Fund (F.W.F.) grant no. I3600-B27 (J.G.D.), grant no. DK W1232\r\n(J.G.D. and J.M.M.)
  and grant no. Z 312-B27, Wittgenstein award (P.J.); the Gesellschaft für Forschungsförderung
  NÖ grant no. LSC18-022 (J.G.D.); an ISTA Interdisciplinary project grant (J.G.D.
  and B.B.); the European Union’s Horizon 2020 research and innovation programme,\r\nMarie-Skłodowska
  Curie grant 665385 (J.M.M. and J.L.); the European Union’s Horizon 2020 research
  and innovation programme, European Research Council grant no. 715767, MATERIALIZABLE
  (B.B.); grant no. 715508, REVERSEAUTISM (G.N.); grant no. 695568, SYNNOVATE (S.G.N.G.);
  and grant no. 692692, GIANTSYN (P.J.); the Simons\r\nFoundation Autism Research
  Initiative grant no. 529085 (S.G.N.G.); the Wellcome Trust Technology Development
  grant no. 202932 (S.G.N.G.); the Marie Skłodowska-Curie Actions Individual Fellowship
  no. 101026635 under the EU Horizon 2020 program (J.F.W.);\r\nthe Human Frontier
  Science Program postdoctoral fellowship LT000557/2018 (W.J.); and the National Science
  Foundation grant no. IIS-1835231 (H.P.) and NCS-FO-2124179 (H.P.)."
article_processing_charge: Yes
article_type: original
author:
- first_name: Philipp
  full_name: Velicky, Philipp
  id: 39BDC62C-F248-11E8-B48F-1D18A9856A87
  last_name: Velicky
  orcid: 0000-0002-2340-7431
- first_name: Eder
  full_name: Miguel Villalba, Eder
  id: 3FB91342-F248-11E8-B48F-1D18A9856A87
  last_name: Miguel Villalba
  orcid: 0000-0001-5665-0430
- first_name: Julia M
  full_name: Michalska, Julia M
  id: 443DB6DE-F248-11E8-B48F-1D18A9856A87
  last_name: Michalska
  orcid: 0000-0003-3862-1235
- first_name: Julia
  full_name: Lyudchik, Julia
  id: 46E28B80-F248-11E8-B48F-1D18A9856A87
  last_name: Lyudchik
- first_name: Donglai
  full_name: Wei, Donglai
  last_name: Wei
- first_name: Zudi
  full_name: Lin, Zudi
  last_name: Lin
- first_name: Jake
  full_name: Watson, Jake
  id: 63836096-4690-11EA-BD4E-32803DDC885E
  last_name: Watson
  orcid: 0000-0002-8698-3823
- first_name: Jakob
  full_name: Troidl, Jakob
  last_name: Troidl
- first_name: Johanna
  full_name: Beyer, Johanna
  last_name: Beyer
- first_name: Yoav
  full_name: Ben Simon, Yoav
  id: 43DF3136-F248-11E8-B48F-1D18A9856A87
  last_name: Ben Simon
- first_name: Christoph M
  full_name: Sommer, Christoph M
  id: 4DF26D8C-F248-11E8-B48F-1D18A9856A87
  last_name: Sommer
  orcid: 0000-0003-1216-9105
- first_name: Wiebke
  full_name: Jahr, Wiebke
  id: 425C1CE8-F248-11E8-B48F-1D18A9856A87
  last_name: Jahr
- first_name: Alban
  full_name: Cenameri, Alban
  id: 9ac8f577-2357-11eb-997a-e566c5550886
  last_name: Cenameri
- first_name: Johannes
  full_name: Broichhagen, Johannes
  last_name: Broichhagen
- first_name: Seth G.N.
  full_name: Grant, Seth G.N.
  last_name: Grant
- first_name: Peter M
  full_name: Jonas, Peter M
  id: 353C1B58-F248-11E8-B48F-1D18A9856A87
  last_name: Jonas
  orcid: 0000-0001-5001-4804
- first_name: Gaia
  full_name: Novarino, Gaia
  id: 3E57A680-F248-11E8-B48F-1D18A9856A87
  last_name: Novarino
  orcid: 0000-0002-7673-7178
- first_name: Hanspeter
  full_name: Pfister, Hanspeter
  last_name: Pfister
- first_name: Bernd
  full_name: Bickel, Bernd
  id: 49876194-F248-11E8-B48F-1D18A9856A87
  last_name: Bickel
  orcid: 0000-0001-6511-9385
- first_name: Johann G
  full_name: Danzl, Johann G
  id: 42EFD3B6-F248-11E8-B48F-1D18A9856A87
  last_name: Danzl
  orcid: 0000-0001-8559-3973
citation:
  ama: Velicky P, Miguel Villalba E, Michalska JM, et al. Dense 4D nanoscale reconstruction
    of living brain tissue. <i>Nature Methods</i>. 2023;20:1256-1265. doi:<a href="https://doi.org/10.1038/s41592-023-01936-6">10.1038/s41592-023-01936-6</a>
  apa: Velicky, P., Miguel Villalba, E., Michalska, J. M., Lyudchik, J., Wei, D.,
    Lin, Z., … Danzl, J. G. (2023). Dense 4D nanoscale reconstruction of living brain
    tissue. <i>Nature Methods</i>. Springer Nature. <a href="https://doi.org/10.1038/s41592-023-01936-6">https://doi.org/10.1038/s41592-023-01936-6</a>
  chicago: Velicky, Philipp, Eder Miguel Villalba, Julia M Michalska, Julia Lyudchik,
    Donglai Wei, Zudi Lin, Jake Watson, et al. “Dense 4D Nanoscale Reconstruction
    of Living Brain Tissue.” <i>Nature Methods</i>. Springer Nature, 2023. <a href="https://doi.org/10.1038/s41592-023-01936-6">https://doi.org/10.1038/s41592-023-01936-6</a>.
  ieee: P. Velicky <i>et al.</i>, “Dense 4D nanoscale reconstruction of living brain
    tissue,” <i>Nature Methods</i>, vol. 20. Springer Nature, pp. 1256–1265, 2023.
  ista: Velicky P, Miguel Villalba E, Michalska JM, Lyudchik J, Wei D, Lin Z, Watson
    J, Troidl J, Beyer J, Ben Simon Y, Sommer CM, Jahr W, Cenameri A, Broichhagen
    J, Grant SGN, Jonas PM, Novarino G, Pfister H, Bickel B, Danzl JG. 2023. Dense
    4D nanoscale reconstruction of living brain tissue. Nature Methods. 20, 1256–1265.
  mla: Velicky, Philipp, et al. “Dense 4D Nanoscale Reconstruction of Living Brain
    Tissue.” <i>Nature Methods</i>, vol. 20, Springer Nature, 2023, pp. 1256–65, doi:<a
    href="https://doi.org/10.1038/s41592-023-01936-6">10.1038/s41592-023-01936-6</a>.
  short: P. Velicky, E. Miguel Villalba, J.M. Michalska, J. Lyudchik, D. Wei, Z. Lin,
    J. Watson, J. Troidl, J. Beyer, Y. Ben Simon, C.M. Sommer, W. Jahr, A. Cenameri,
    J. Broichhagen, S.G.N. Grant, P.M. Jonas, G. Novarino, H. Pfister, B. Bickel,
    J.G. Danzl, Nature Methods 20 (2023) 1256–1265.
date_created: 2023-07-23T22:01:13Z
date_published: 2023-08-01T00:00:00Z
date_updated: 2024-01-10T08:37:48Z
day: '01'
department:
- _id: PeJo
- _id: GaNo
- _id: BeBi
- _id: JoDa
- _id: Bio
doi: 10.1038/s41592-023-01936-6
ec_funded: 1
external_id:
  isi:
  - '001025621500001'
  pmid:
  - '37429995'
intvolume: '        20'
isi: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://doi.org/10.1038/s41592-023-01936-6
month: '08'
oa: 1
oa_version: Published Version
page: 1256-1265
pmid: 1
project:
- _id: 265CB4D0-B435-11E9-9278-68D0E5697425
  call_identifier: FWF
  grant_number: I03600
  name: Optical control of synaptic function via adhesion molecules
- _id: 2548AE96-B435-11E9-9278-68D0E5697425
  call_identifier: FWF
  grant_number: W1232-B24
  name: Molecular Drug Targets
- _id: 25C5A090-B435-11E9-9278-68D0E5697425
  call_identifier: FWF
  grant_number: Z00312
  name: The Wittgenstein Prize
- _id: 23889792-32DE-11EA-91FC-C7463DDC885E
  name: High content imaging to decode human immune cell interactions in health and
    allergic disease
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
  grant_number: '665385'
  name: International IST Doctoral Program
- _id: 24F9549A-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
  grant_number: '715767'
  name: 'MATERIALIZABLE: Intelligent fabrication-oriented Computational Design and
    Modeling'
- _id: 25444568-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
  grant_number: '715508'
  name: Probing the Reversibility of Autism Spectrum Disorders by Employing in vivo
    and in vitro Models
- _id: 25B7EB9E-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
  grant_number: '692692'
  name: Biophysics and circuit function of a giant cortical glumatergic synapse
- _id: fc2be41b-9c52-11eb-aca3-faa90aa144e9
  call_identifier: H2020
  grant_number: '101026635'
  name: Synaptic computations of the hippocampal CA3 circuitry
- _id: 2668BFA0-B435-11E9-9278-68D0E5697425
  grant_number: LT00057
  name: High-speed 3D-nanoscopy to study the role of adhesion during 3D cell migration
publication: Nature Methods
publication_identifier:
  eissn:
  - 1548-7105
  issn:
  - 1548-7091
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
related_material:
  link:
  - relation: software
    url: https://github.com/danzllab/LIONESS
  record:
  - id: '12817'
    relation: research_data
    status: public
  - id: '14770'
    relation: shorter_version
    status: public
scopus_import: '1'
status: public
title: Dense 4D nanoscale reconstruction of living brain tissue
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 20
year: '2023'
...
