---
_id: '9794'
abstract:
- lang: eng
text: 'Lymph nodes (LNs) comprise two main structural elements: fibroblastic reticular
cells that form dedicated niches for immune cell interaction and capsular fibroblasts
that build a shell around the organ. Immunological challenge causes LNs to increase
more than tenfold in size within a few days. Here, we characterized the biomechanics
of LN swelling on the cellular and organ scale. We identified lymphocyte trapping
by influx and proliferation as drivers of an outward pressure force, causing fibroblastic
reticular cells of the T-zone (TRCs) and their associated conduits to stretch.
After an initial phase of relaxation, TRCs sensed the resulting strain through
cell matrix adhesions, which coordinated local growth and remodeling of the stromal
network. While the expanded TRC network readopted its typical configuration, a
massive fibrotic reaction of the organ capsule set in and countered further organ
expansion. Thus, different fibroblast populations mechanically control LN swelling
in a multitier fashion.'
acknowledged_ssus:
- _id: Bio
- _id: EM-Fac
- _id: PreCl
- _id: LifeSc
acknowledgement: This research was supported by the Scientific Service Units of IST
Austria through resources provided by the Imaging and Optics, Electron Microscopy,
Preclinical and Life Science Facilities. We thank C. Moussion for providing anti-PNAd
antibody and D. Critchley for Talin1-floxed mice, and E. Papusheva for providing
a custom 3D channel alignment script. This work was supported by a European Research
Council grant ERC-CoG-72437 to M.S. M.H. was supported by Czech Sciencundation GACR
20-24603Y and Charles University PRIMUS/20/MED/013.
article_processing_charge: No
article_type: original
author:
- first_name: Frank P
full_name: Assen, Frank P
id: 3A8E7F24-F248-11E8-B48F-1D18A9856A87
last_name: Assen
orcid: 0000-0003-3470-6119
- first_name: Jun
full_name: Abe, Jun
last_name: Abe
- first_name: Miroslav
full_name: Hons, Miroslav
id: 4167FE56-F248-11E8-B48F-1D18A9856A87
last_name: Hons
orcid: 0000-0002-6625-3348
- first_name: Robert
full_name: Hauschild, Robert
id: 4E01D6B4-F248-11E8-B48F-1D18A9856A87
last_name: Hauschild
orcid: 0000-0001-9843-3522
- first_name: Shayan
full_name: Shamipour, Shayan
id: 40B34FE2-F248-11E8-B48F-1D18A9856A87
last_name: Shamipour
- first_name: Walter
full_name: Kaufmann, Walter
id: 3F99E422-F248-11E8-B48F-1D18A9856A87
last_name: Kaufmann
orcid: 0000-0001-9735-5315
- first_name: Tommaso
full_name: Costanzo, Tommaso
id: D93824F4-D9BA-11E9-BB12-F207E6697425
last_name: Costanzo
orcid: 0000-0001-9732-3815
- first_name: Gabriel
full_name: Krens, Gabriel
id: 2B819732-F248-11E8-B48F-1D18A9856A87
last_name: Krens
orcid: 0000-0003-4761-5996
- first_name: Markus
full_name: Brown, Markus
id: 3DAB9AFC-F248-11E8-B48F-1D18A9856A87
last_name: Brown
- first_name: Burkhard
full_name: Ludewig, Burkhard
last_name: Ludewig
- first_name: Simon
full_name: Hippenmeyer, Simon
id: 37B36620-F248-11E8-B48F-1D18A9856A87
last_name: Hippenmeyer
orcid: 0000-0003-2279-1061
- first_name: Carl-Philipp J
full_name: Heisenberg, Carl-Philipp J
id: 39427864-F248-11E8-B48F-1D18A9856A87
last_name: Heisenberg
orcid: 0000-0002-0912-4566
- first_name: Wolfgang
full_name: Weninger, Wolfgang
last_name: Weninger
- first_name: Edouard B
full_name: Hannezo, Edouard B
id: 3A9DB764-F248-11E8-B48F-1D18A9856A87
last_name: Hannezo
orcid: 0000-0001-6005-1561
- first_name: Sanjiv A.
full_name: Luther, Sanjiv A.
last_name: Luther
- first_name: Jens V.
full_name: Stein, Jens V.
last_name: Stein
- first_name: Michael K
full_name: Sixt, Michael K
id: 41E9FBEA-F248-11E8-B48F-1D18A9856A87
last_name: Sixt
orcid: 0000-0002-4561-241X
citation:
ama: Assen FP, Abe J, Hons M, et al. Multitier mechanics control stromal adaptations
in swelling lymph nodes. Nature Immunology. 2022;23:1246-1255. doi:10.1038/s41590-022-01257-4
apa: Assen, F. P., Abe, J., Hons, M., Hauschild, R., Shamipour, S., Kaufmann, W.,
… Sixt, M. K. (2022). Multitier mechanics control stromal adaptations in swelling
lymph nodes. Nature Immunology. Springer Nature. https://doi.org/10.1038/s41590-022-01257-4
chicago: Assen, Frank P, Jun Abe, Miroslav Hons, Robert Hauschild, Shayan Shamipour,
Walter Kaufmann, Tommaso Costanzo, et al. “Multitier Mechanics Control Stromal
Adaptations in Swelling Lymph Nodes.” Nature Immunology. Springer Nature,
2022. https://doi.org/10.1038/s41590-022-01257-4.
ieee: F. P. Assen et al., “Multitier mechanics control stromal adaptations
in swelling lymph nodes,” Nature Immunology, vol. 23. Springer Nature,
pp. 1246–1255, 2022.
ista: Assen FP, Abe J, Hons M, Hauschild R, Shamipour S, Kaufmann W, Costanzo T,
Krens G, Brown M, Ludewig B, Hippenmeyer S, Heisenberg C-PJ, Weninger W, Hannezo
EB, Luther SA, Stein JV, Sixt MK. 2022. Multitier mechanics control stromal adaptations
in swelling lymph nodes. Nature Immunology. 23, 1246–1255.
mla: Assen, Frank P., et al. “Multitier Mechanics Control Stromal Adaptations in
Swelling Lymph Nodes.” Nature Immunology, vol. 23, Springer Nature, 2022,
pp. 1246–55, doi:10.1038/s41590-022-01257-4.
short: F.P. Assen, J. Abe, M. Hons, R. Hauschild, S. Shamipour, W. Kaufmann, T.
Costanzo, G. Krens, M. Brown, B. Ludewig, S. Hippenmeyer, C.-P.J. Heisenberg,
W. Weninger, E.B. Hannezo, S.A. Luther, J.V. Stein, M.K. Sixt, Nature Immunology
23 (2022) 1246–1255.
date_created: 2021-08-06T09:09:11Z
date_published: 2022-07-11T00:00:00Z
date_updated: 2023-08-02T06:53:07Z
day: '11'
ddc:
- '570'
department:
- _id: SiHi
- _id: CaHe
- _id: EdHa
- _id: EM-Fac
- _id: Bio
- _id: MiSi
doi: 10.1038/s41590-022-01257-4
ec_funded: 1
external_id:
isi:
- '000822975900002'
file:
- access_level: open_access
checksum: 628e7b49809f22c75b428842efe70c68
content_type: application/pdf
creator: dernst
date_created: 2022-07-25T07:11:32Z
date_updated: 2022-07-25T07:11:32Z
file_id: '11642'
file_name: 2022_NatureImmunology_Assen.pdf
file_size: 11475325
relation: main_file
success: 1
file_date_updated: 2022-07-25T07:11:32Z
has_accepted_license: '1'
intvolume: ' 23'
isi: 1
language:
- iso: eng
month: '07'
oa: 1
oa_version: Published Version
page: 1246-1255
project:
- _id: 25FE9508-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '724373'
name: Cellular navigation along spatial gradients
publication: Nature Immunology
publication_identifier:
eissn:
- 1529-2916
issn:
- 1529-2908
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: Multitier mechanics control stromal adaptations in swelling lymph nodes
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: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 23
year: '2022'
...
---
_id: '9955'
abstract:
- lang: eng
text: Neurons can change their classical neurotransmitters during ontogeny, sometimes
going through stages of dual release. Here, we explored the development of the
neurotransmitter identity of neurons of the avian nucleus isthmi parvocellularis
(Ipc), whose axon terminals are retinotopically arranged in the optic tectum (TeO)
and exert a focal gating effect upon the ascending transmission of retinal inputs.
Although cholinergic and glutamatergic markers are both found in Ipc neurons and
terminals of adult pigeons and chicks, the mRNA expression of the vesicular acetylcholine
transporter, VAChT, is weak or absent. To explore how the Ipc neurotransmitter
identity is established during ontogeny, we analyzed the expression of mRNAs coding
for cholinergic (ChAT, VAChT, and CHT) and glutamatergic (VGluT2 and VGluT3) markers
in chick embryos at different developmental stages. We found that between E12
and E18, Ipc neurons expressed all cholinergic mRNAs and also VGluT2 mRNA; however,
from E16 through posthatch stages, VAChT mRNA expression was specifically diminished.
Our ex vivo deposits of tracer crystals and intracellular filling experiments
revealed that Ipc axons exhibit a mature paintbrush morphology late in development,
experiencing marked morphological transformations during the period of presumptive
dual vesicular transmitter release. Additionally, although ChAT protein immunoassays
increasingly label the growing Ipc axon, this labeling was consistently restricted
to sparse portions of the terminal branches. Combined, these results suggest that
the synthesis of glutamate and acetylcholine, and their vesicular release, is
complexly linked to the developmental processes of branching, growing and remodeling
of these unique axons.
acknowledgement: 'This work was supported by FONDECYT grants 1151432 and 1210169 to
Gonzalo J. Marín. FONDECYT grant 1210069 to Jorge Mpodozis. Spanish Ministry of
Science, Innovation and Universities (MCIU), State Research Agency (AEI) and European
Regional Development Fund (FEDER), PGC2018-098229-B-100 to José L Ferrán. Spanish
Ministry of Economy and Competitiveness Excellency Grant BFU2014-57516P (with European
Community FEDER support), and a Seneca Foundation (Autonomous Community of Murcia)
Excellency Research contract, ref: 19904/ GERM/15; project name: Genoarchitectonic
Brain Development and Applications to Neurodegenerative Diseases and Cancer (5672
Fundación Séneca) to Luis Puelles. The authors gratefully acknowledge the valuable
editorial help provided by Sara Fernández-Collemann. The authors also thank Elisa
Sentis and Solano Henríquez for expert technical help.'
article_processing_charge: No
article_type: original
author:
- first_name: Rosana
full_name: Reyes‐Pinto, Rosana
last_name: Reyes‐Pinto
- first_name: José L.
full_name: Ferrán, José L.
last_name: Ferrán
- first_name: Tomas A
full_name: Vega Zuniga, Tomas A
id: 2E7C4E78-F248-11E8-B48F-1D18A9856A87
last_name: Vega Zuniga
- first_name: Cristian
full_name: González‐Cabrera, Cristian
last_name: González‐Cabrera
- first_name: Harald
full_name: Luksch, Harald
last_name: Luksch
- first_name: Jorge
full_name: Mpodozis, Jorge
last_name: Mpodozis
- first_name: Luis
full_name: Puelles, Luis
last_name: Puelles
- first_name: Gonzalo J.
full_name: Marín, Gonzalo J.
last_name: Marín
citation:
ama: Reyes‐Pinto R, Ferrán JL, Vega Zuniga TA, et al. Change in the neurochemical
signature and morphological development of the parvocellular isthmic projection
to the avian tectum. Journal of Comparative Neurology. 2022;530(2):553-573.
doi:10.1002/cne.25229
apa: Reyes‐Pinto, R., Ferrán, J. L., Vega Zuniga, T. A., González‐Cabrera, C., Luksch,
H., Mpodozis, J., … Marín, G. J. (2022). Change in the neurochemical signature
and morphological development of the parvocellular isthmic projection to the avian
tectum. Journal of Comparative Neurology. Wiley. https://doi.org/10.1002/cne.25229
chicago: Reyes‐Pinto, Rosana, José L. Ferrán, Tomas A Vega Zuniga, Cristian González‐Cabrera,
Harald Luksch, Jorge Mpodozis, Luis Puelles, and Gonzalo J. Marín. “Change in
the Neurochemical Signature and Morphological Development of the Parvocellular
Isthmic Projection to the Avian Tectum.” Journal of Comparative Neurology.
Wiley, 2022. https://doi.org/10.1002/cne.25229.
ieee: R. Reyes‐Pinto et al., “Change in the neurochemical signature and morphological
development of the parvocellular isthmic projection to the avian tectum,” Journal
of Comparative Neurology, vol. 530, no. 2. Wiley, pp. 553–573, 2022.
ista: Reyes‐Pinto R, Ferrán JL, Vega Zuniga TA, González‐Cabrera C, Luksch H, Mpodozis
J, Puelles L, Marín GJ. 2022. Change in the neurochemical signature and morphological
development of the parvocellular isthmic projection to the avian tectum. Journal
of Comparative Neurology. 530(2), 553–573.
mla: Reyes‐Pinto, Rosana, et al. “Change in the Neurochemical Signature and Morphological
Development of the Parvocellular Isthmic Projection to the Avian Tectum.” Journal
of Comparative Neurology, vol. 530, no. 2, Wiley, 2022, pp. 553–73, doi:10.1002/cne.25229.
short: R. Reyes‐Pinto, J.L. Ferrán, T.A. Vega Zuniga, C. González‐Cabrera, H. Luksch,
J. Mpodozis, L. Puelles, G.J. Marín, Journal of Comparative Neurology 530 (2022)
553–573.
date_created: 2021-08-23T08:40:59Z
date_published: 2022-02-01T00:00:00Z
date_updated: 2023-08-11T10:58:17Z
day: '01'
department:
- _id: MaJö
doi: 10.1002/cne.25229
external_id:
isi:
- '000686420000001'
pmid:
- '34363623'
intvolume: ' 530'
isi: 1
issue: '2'
language:
- iso: eng
month: '02'
oa_version: None
page: 553-573
pmid: 1
publication: Journal of Comparative Neurology
publication_identifier:
eissn:
- 1096-9861
issn:
- 0021-9967
publication_status: published
publisher: Wiley
quality_controlled: '1'
scopus_import: '1'
status: public
title: Change in the neurochemical signature and morphological development of the
parvocellular isthmic projection to the avian tectum
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 530
year: '2022'
...
---
_id: '9977'
abstract:
- lang: eng
text: "For a Seifert fibered homology sphere X we show that the q-series invariant
Zˆ0(X; q) introduced by Gukov-Pei-Putrov-Vafa, is a resummation of the Ohtsuki
series Z0(X). We show that for every even k ∈ N there exists a full asymptotic
expansion of Zˆ0(X; q) for q tending to e 2πi/k, and in particular that the limit
Zˆ0(X; e 2πi/k) exists and is equal to the\r\nWRT quantum invariant τk(X). We
show that the poles of the Borel transform of Z0(X) coincide with the classical
complex Chern-Simons values, which we further show classifies the corresponding
components of the moduli space of flat SL(2, C)-connections."
acknowledgement: "We warmly thank S. Gukov for valuable discussions on the GPPV invariant
̂Z\U0001D44E(\U0001D4403; \U0001D45E). The first\r\nauthor was supported in part
by the center of excellence grant ‘Center for Quantum Geometry\r\nof Moduli Spaces’
from the Danish National Research Foundation (DNRF95) and by the ERCSynergy\r\ngrant
‘ReNewQuantum’. The second author received funding from the European Union’s Horizon
2020 research and innovation program under the Marie Skłodowska-Curie grant agreement
no. 754411."
article_processing_charge: Yes (via OA deal)
article_type: original
arxiv: 1
author:
- first_name: William
full_name: Mistegaard, William
id: 41B03CD0-62AE-11E9-84EF-0718E6697425
last_name: Mistegaard
- first_name: Jørgen Ellegaard
full_name: Andersen, Jørgen Ellegaard
last_name: Andersen
citation:
ama: Mistegaard W, Andersen JE. Resurgence analysis of quantum invariants of Seifert
fibered homology spheres. Journal of the London Mathematical Society. 2022;105(2):709-764.
doi:10.1112/jlms.12506
apa: Mistegaard, W., & Andersen, J. E. (2022). Resurgence analysis of quantum
invariants of Seifert fibered homology spheres. Journal of the London Mathematical
Society. Wiley. https://doi.org/10.1112/jlms.12506
chicago: Mistegaard, William, and Jørgen Ellegaard Andersen. “Resurgence Analysis
of Quantum Invariants of Seifert Fibered Homology Spheres.” Journal of the
London Mathematical Society. Wiley, 2022. https://doi.org/10.1112/jlms.12506.
ieee: W. Mistegaard and J. E. Andersen, “Resurgence analysis of quantum invariants
of Seifert fibered homology spheres,” Journal of the London Mathematical Society,
vol. 105, no. 2. Wiley, pp. 709–764, 2022.
ista: Mistegaard W, Andersen JE. 2022. Resurgence analysis of quantum invariants
of Seifert fibered homology spheres. Journal of the London Mathematical Society.
105(2), 709–764.
mla: Mistegaard, William, and Jørgen Ellegaard Andersen. “Resurgence Analysis of
Quantum Invariants of Seifert Fibered Homology Spheres.” Journal of the London
Mathematical Society, vol. 105, no. 2, Wiley, 2022, pp. 709–64, doi:10.1112/jlms.12506.
short: W. Mistegaard, J.E. Andersen, Journal of the London Mathematical Society
105 (2022) 709–764.
date_created: 2021-08-31T12:51:40Z
date_published: 2022-03-01T00:00:00Z
date_updated: 2023-08-02T06:53:51Z
day: '01'
ddc:
- '510'
department:
- _id: TaHa
doi: 10.1112/jlms.12506
ec_funded: 1
external_id:
arxiv:
- '1811.05376'
isi:
- '000755205700001'
file:
- access_level: open_access
checksum: 9c72327d39f34f1a6eaa98fa4b8493f2
content_type: application/pdf
creator: dernst
date_created: 2022-03-24T11:42:25Z
date_updated: 2022-03-24T11:42:25Z
file_id: '10917'
file_name: 2022_JourLondonMathSoc_Andersen.pdf
file_size: 649130
relation: main_file
success: 1
file_date_updated: 2022-03-24T11:42:25Z
has_accepted_license: '1'
intvolume: ' 105'
isi: 1
issue: '2'
language:
- iso: eng
month: '03'
oa: 1
oa_version: Published Version
page: 709-764
project:
- _id: 260C2330-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '754411'
name: ISTplus - Postdoctoral Fellowships
publication: Journal of the London Mathematical Society
publication_identifier:
eissn:
- 1469-7750
publication_status: published
publisher: Wiley
quality_controlled: '1'
scopus_import: '1'
status: public
title: Resurgence analysis of quantum invariants of Seifert fibered homology spheres
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: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 105
year: '2022'
...
---
_id: '10665'
abstract:
- lang: eng
text: "Formal verification of neural networks is an active topic of research, and
recent advances have significantly increased the size of the networks that verification
tools can handle. However, most methods are designed for verification of an idealized
model of the actual network which works over real arithmetic and ignores rounding
imprecisions. This idealization is in stark contrast to network quantization,
which is a technique that trades numerical precision for computational efficiency
and is, therefore, often applied in practice. Neglecting rounding errors of such
low-bit quantized neural networks has been shown to lead to wrong conclusions
about the network’s correctness. Thus, the desired approach for verifying quantized
neural networks would be one that takes these rounding errors\r\ninto account.
In this paper, we show that verifying the bitexact implementation of quantized
neural networks with bitvector specifications is PSPACE-hard, even though verifying
idealized real-valued networks and satisfiability of bit-vector specifications
alone are each in NP. Furthermore, we explore several practical heuristics toward
closing the complexity gap between idealized and bit-exact verification. In particular,
we propose three techniques for making SMT-based verification of quantized neural
networks more scalable. Our experiments demonstrate that our proposed methods
allow a speedup of up to three orders of magnitude over existing approaches."
acknowledgement: "This research was supported in part by the Austrian Science Fund
(FWF) under grant Z211-N23 (Wittgenstein\r\nAward), 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.\r\n"
alternative_title:
- Technical Tracks
article_processing_charge: No
arxiv: 1
author:
- 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: 'Henzinger TA, Lechner M, Zikelic D. Scalable verification of quantized neural
networks. In: Proceedings of the AAAI Conference on Artificial Intelligence.
Vol 35. AAAI Press; 2021:3787-3795.'
apa: 'Henzinger, T. A., Lechner, M., & Zikelic, D. (2021). Scalable verification
of quantized neural networks. In Proceedings of the AAAI Conference on Artificial
Intelligence (Vol. 35, pp. 3787–3795). Virtual: AAAI Press.'
chicago: Henzinger, Thomas A, Mathias Lechner, and Dorde Zikelic. “Scalable Verification
of Quantized Neural Networks.” In Proceedings of the AAAI Conference on Artificial
Intelligence, 35:3787–95. AAAI Press, 2021.
ieee: T. A. Henzinger, M. Lechner, and D. Zikelic, “Scalable verification of quantized
neural networks,” in Proceedings of the AAAI Conference on Artificial Intelligence,
Virtual, 2021, vol. 35, no. 5A, pp. 3787–3795.
ista: 'Henzinger TA, Lechner M, Zikelic D. 2021. Scalable verification of quantized
neural networks. Proceedings of the AAAI Conference on Artificial Intelligence.
AAAI: Association for the Advancement of Artificial Intelligence, Technical Tracks,
vol. 35, 3787–3795.'
mla: Henzinger, Thomas A., et al. “Scalable Verification of Quantized Neural Networks.”
Proceedings of the AAAI Conference on Artificial Intelligence, vol. 35,
no. 5A, AAAI Press, 2021, pp. 3787–95.
short: T.A. Henzinger, M. Lechner, D. Zikelic, in:, Proceedings of the AAAI Conference
on Artificial Intelligence, AAAI Press, 2021, pp. 3787–3795.
conference:
end_date: 2021-02-09
location: Virtual
name: 'AAAI: Association for the Advancement of Artificial Intelligence'
start_date: 2021-02-02
date_created: 2022-01-25T15:15:02Z
date_published: 2021-05-28T00:00:00Z
date_updated: 2025-07-14T09:10:11Z
day: '28'
ddc:
- '000'
department:
- _id: GradSch
- _id: ToHe
ec_funded: 1
external_id:
arxiv:
- '2012.08185'
file:
- access_level: open_access
checksum: 2bc8155b2526a70fba5b7301bc89dbd1
content_type: application/pdf
creator: mlechner
date_created: 2022-01-26T07:41:16Z
date_updated: 2022-01-26T07:41:16Z
file_id: '10684'
file_name: 16496-Article Text-19990-1-2-20210518 (1).pdf
file_size: 137235
relation: main_file
success: 1
file_date_updated: 2022-01-26T07:41:16Z
has_accepted_license: '1'
intvolume: ' 35'
issue: 5A
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://ojs.aaai.org/index.php/AAAI/article/view/16496
month: '05'
oa: 1
oa_version: Published Version
page: 3787-3795
project:
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '665385'
name: International IST Doctoral Program
- _id: 25F42A32-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: Z211
name: The Wittgenstein Prize
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
publication: Proceedings of the AAAI Conference on Artificial Intelligence
publication_identifier:
eissn:
- 2374-3468
isbn:
- 978-1-57735-866-4
issn:
- 2159-5399
publication_status: published
publisher: AAAI Press
quality_controlled: '1'
related_material:
record:
- id: '11362'
relation: dissertation_contains
status: public
scopus_import: '1'
status: public
title: Scalable verification of quantized neural networks
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 35
year: '2021'
...
---
_id: '10666'
abstract:
- lang: eng
text: Adversarial training is an effective method to train deep learning models
that are resilient to norm-bounded perturbations, with the cost of nominal performance
drop. While adversarial training appears to enhance the robustness and safety
of a deep model deployed in open-world decision-critical applications, counterintuitively,
it induces undesired behaviors in robot learning settings. In this paper, we show
theoretically and experimentally that neural controllers obtained via adversarial
training are subjected to three types of defects, namely transient, systematic,
and conditional errors. We first generalize adversarial training to a safety-domain
optimization scheme allowing for more generic specifications. We then prove that
such a learning process tends to cause certain error profiles. We support our
theoretical results by a thorough experimental safety analysis in a robot-learning
task. Our results suggest that adversarial training is not yet ready for robot
learning.
acknowledgement: M.L. and T.A.H. are supported in part by the Austrian Science Fund
(FWF) under grant Z211-N23 (Wittgenstein Award). R.H. and D.R. are supported by
Boeing and R.G. by Horizon-2020 ECSEL Project grant no. 783163 (iDev40).
article_processing_charge: No
arxiv: 1
author:
- first_name: Mathias
full_name: Lechner, Mathias
id: 3DC22916-F248-11E8-B48F-1D18A9856A87
last_name: Lechner
- first_name: Ramin
full_name: Hasani, Ramin
last_name: Hasani
- first_name: Radu
full_name: Grosu, Radu
last_name: Grosu
- first_name: Daniela
full_name: Rus, Daniela
last_name: Rus
- first_name: Thomas A
full_name: Henzinger, Thomas A
id: 40876CD8-F248-11E8-B48F-1D18A9856A87
last_name: Henzinger
orcid: 0000-0002-2985-7724
citation:
ama: 'Lechner M, Hasani R, Grosu R, Rus D, Henzinger TA. Adversarial training is
not ready for robot learning. In: 2021 IEEE International Conference on Robotics
and Automation. ICRA. ; 2021:4140-4147. doi:10.1109/ICRA48506.2021.9561036'
apa: Lechner, M., Hasani, R., Grosu, R., Rus, D., & Henzinger, T. A. (2021).
Adversarial training is not ready for robot learning. In 2021 IEEE International
Conference on Robotics and Automation (pp. 4140–4147). Xi’an, China. https://doi.org/10.1109/ICRA48506.2021.9561036
chicago: Lechner, Mathias, Ramin Hasani, Radu Grosu, Daniela Rus, and Thomas A Henzinger.
“Adversarial Training Is Not Ready for Robot Learning.” In 2021 IEEE International
Conference on Robotics and Automation, 4140–47. ICRA, 2021. https://doi.org/10.1109/ICRA48506.2021.9561036.
ieee: M. Lechner, R. Hasani, R. Grosu, D. Rus, and T. A. Henzinger, “Adversarial
training is not ready for robot learning,” in 2021 IEEE International Conference
on Robotics and Automation, Xi’an, China, 2021, pp. 4140–4147.
ista: 'Lechner M, Hasani R, Grosu R, Rus D, Henzinger TA. 2021. Adversarial training
is not ready for robot learning. 2021 IEEE International Conference on Robotics
and Automation. ICRA: International Conference on Robotics and AutomationICRA,
4140–4147.'
mla: Lechner, Mathias, et al. “Adversarial Training Is Not Ready for Robot Learning.”
2021 IEEE International Conference on Robotics and Automation, 2021, pp.
4140–47, doi:10.1109/ICRA48506.2021.9561036.
short: M. Lechner, R. Hasani, R. Grosu, D. Rus, T.A. Henzinger, in:, 2021 IEEE International
Conference on Robotics and Automation, 2021, pp. 4140–4147.
conference:
end_date: 2021-06-05
location: Xi'an, China
name: 'ICRA: International Conference on Robotics and Automation'
start_date: 2021-05-30
date_created: 2022-01-25T15:44:54Z
date_published: 2021-01-01T00:00:00Z
date_updated: 2023-08-17T06:58:38Z
ddc:
- '000'
department:
- _id: GradSch
- _id: ToHe
doi: 10.1109/ICRA48506.2021.9561036
external_id:
arxiv:
- '2103.08187'
isi:
- '000765738803040'
has_accepted_license: '1'
isi: 1
language:
- iso: eng
license: https://creativecommons.org/licenses/by-nc-nd/3.0/
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2103.08187
oa: 1
oa_version: None
page: 4140-4147
project:
- _id: 25F42A32-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: Z211
name: The Wittgenstein Prize
publication: 2021 IEEE International Conference on Robotics and Automation
publication_identifier:
eisbn:
- 978-1-7281-9077-8
eissn:
- 2577-087X
isbn:
- 978-1-7281-9078-5
issn:
- 1050-4729
publication_status: published
quality_controlled: '1'
related_material:
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relation: dissertation_contains
status: public
series_title: ICRA
status: public
title: Adversarial training is not ready for robot learning
tmp:
image: /images/cc_by_nc_nd.png
legal_code_url: https://creativecommons.org/licenses/by-nc-nd/3.0/legalcode
name: Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND
3.0)
short: CC BY-NC-ND (3.0)
type: conference
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
year: '2021'
...
---
_id: '10667'
abstract:
- lang: eng
text: Bayesian neural networks (BNNs) place distributions over the weights of a
neural network to model uncertainty in the data and the network's prediction.
We consider the problem of verifying safety when running a Bayesian neural network
policy in a feedback loop with infinite time horizon systems. Compared to the
existing sampling-based approaches, which are inapplicable to the infinite time
horizon setting, we train a separate deterministic neural network that serves
as an infinite time horizon safety certificate. In particular, we show that the
certificate network guarantees the safety of the system over a subset of the BNN
weight posterior's support. Our method first computes a safe weight set and then
alters the BNN's weight posterior to reject samples outside this set. Moreover,
we show how to extend our approach to a safe-exploration reinforcement learning
setting, in order to avoid unsafe trajectories during the training of the policy.
We evaluate our approach on a series of reinforcement learning benchmarks, including
non-Lyapunovian safety specifications.
acknowledgement: This research was supported in part by the Austrian Science Fund
(FWF) under grant Z211-N23 (Wittgenstein Award), 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:
- ' Advances in Neural Information Processing Systems'
article_processing_charge: No
arxiv: 1
author:
- first_name: Mathias
full_name: Lechner, Mathias
id: 3DC22916-F248-11E8-B48F-1D18A9856A87
last_name: Lechner
- first_name: Ðorđe
full_name: Žikelić, Ðorđe
last_name: Žikelić
- 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
citation:
ama: 'Lechner M, Žikelić Ð, Chatterjee K, Henzinger TA. Infinite time horizon safety
of Bayesian neural networks. In: 35th Conference on Neural Information Processing
Systems. ; 2021. doi:10.48550/arXiv.2111.03165'
apa: Lechner, M., Žikelić, Ð., Chatterjee, K., & Henzinger, T. A. (2021). Infinite
time horizon safety of Bayesian neural networks. In 35th Conference on Neural
Information Processing Systems. Virtual. https://doi.org/10.48550/arXiv.2111.03165
chicago: Lechner, Mathias, Ðorđe Žikelić, Krishnendu Chatterjee, and Thomas A Henzinger.
“Infinite Time Horizon Safety of Bayesian Neural Networks.” In 35th Conference
on Neural Information Processing Systems, 2021. https://doi.org/10.48550/arXiv.2111.03165.
ieee: M. Lechner, Ð. Žikelić, K. Chatterjee, and T. A. Henzinger, “Infinite time
horizon safety of Bayesian neural networks,” in 35th Conference on Neural Information
Processing Systems, Virtual, 2021.
ista: 'Lechner M, Žikelić Ð, Chatterjee K, Henzinger TA. 2021. Infinite time horizon
safety of Bayesian neural networks. 35th Conference on Neural Information Processing
Systems. NeurIPS: Neural Information Processing Systems, Advances in Neural Information
Processing Systems, .'
mla: Lechner, Mathias, et al. “Infinite Time Horizon Safety of Bayesian Neural Networks.”
35th Conference on Neural Information Processing Systems, 2021, doi:10.48550/arXiv.2111.03165.
short: M. Lechner, Ð. Žikelić, K. Chatterjee, T.A. Henzinger, in:, 35th Conference
on Neural Information Processing Systems, 2021.
conference:
end_date: 2021-12-10
location: Virtual
name: 'NeurIPS: Neural Information Processing Systems'
start_date: 2021-12-06
date_created: 2022-01-25T15:45:58Z
date_published: 2021-12-01T00:00:00Z
date_updated: 2025-07-14T09:10:12Z
day: '01'
ddc:
- '000'
department:
- _id: GradSch
- _id: ToHe
- _id: KrCh
doi: 10.48550/arXiv.2111.03165
ec_funded: 1
external_id:
arxiv:
- '2111.03165'
file:
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checksum: 0fc0f852525c10dda9cc9ffea07fb4e4
content_type: application/pdf
creator: mlechner
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date_updated: 2022-01-26T07:39:59Z
file_id: '10682'
file_name: infinite_time_horizon_safety_o.pdf
file_size: 452492
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success: 1
file_date_updated: 2022-01-26T07:39:59Z
has_accepted_license: '1'
language:
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main_file_link:
- open_access: '1'
url: https://proceedings.neurips.cc/paper/2021/hash/544defa9fddff50c53b71c43e0da72be-Abstract.html
month: '12'
oa: 1
oa_version: Published Version
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'
- _id: 25F42A32-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: Z211
name: The Wittgenstein Prize
publication: 35th Conference on Neural Information Processing Systems
publication_status: published
quality_controlled: '1'
related_material:
record:
- id: '11362'
relation: dissertation_contains
status: public
status: public
title: Infinite time horizon safety of Bayesian neural networks
tmp:
image: /images/cc_by_nc_nd.png
legal_code_url: https://creativecommons.org/licenses/by-nc-nd/3.0/legalcode
name: Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND
3.0)
short: CC BY-NC-ND (3.0)
type: conference
user_id: 2EBD1598-F248-11E8-B48F-1D18A9856A87
year: '2021'
...
---
_id: '10668'
abstract:
- lang: eng
text: 'Robustness to variations in lighting conditions is a key objective for any
deep vision system. To this end, our paper extends the receptive field of convolutional
neural networks with two residual components, ubiquitous in the visual processing
system of vertebrates: On-center and off-center pathways, with an excitatory center
and inhibitory surround; OOCS for short. The On-center pathway is excited by the
presence of a light stimulus in its center, but not in its surround, whereas the
Off-center pathway is excited by the absence of a light stimulus in its center,
but not in its surround. We design OOCS pathways via a difference of Gaussians,
with their variance computed analytically from the size of the receptive fields.
OOCS pathways complement each other in their response to light stimuli, ensuring
this way a strong edge-detection capability, and as a result an accurate and robust
inference under challenging lighting conditions. We provide extensive empirical
evidence showing that networks supplied with OOCS pathways gain accuracy and illumination-robustness
from the novel edge representation, compared to other baselines.'
acknowledgement: Z.B. is supported by the Doctoral College Resilient Embedded Systems,
which is run jointly by the TU Wien’s Faculty of Informatics and the UAS Technikum
Wien. R.G. is partially supported by the Horizon 2020 Era-Permed project Persorad,
and ECSEL Project grant no. 783163 (iDev40). R.H and D.R were partially supported
by Boeing and MIT. M.L. is supported in part by the Austrian Science Fund (FWF)
under grant Z211-N23 (Wittgenstein Award).
alternative_title:
- PMLR
article_processing_charge: No
author:
- first_name: Zahra
full_name: Babaiee, Zahra
last_name: Babaiee
- first_name: Ramin
full_name: Hasani, Ramin
last_name: Hasani
- first_name: Mathias
full_name: Lechner, Mathias
id: 3DC22916-F248-11E8-B48F-1D18A9856A87
last_name: Lechner
- first_name: Daniela
full_name: Rus, Daniela
last_name: Rus
- first_name: Radu
full_name: Grosu, Radu
last_name: Grosu
citation:
ama: 'Babaiee Z, Hasani R, Lechner M, Rus D, Grosu R. On-off center-surround receptive
fields for accurate and robust image classification. In: Proceedings of the
38th International Conference on Machine Learning. Vol 139. ML Research Press;
2021:478-489.'
apa: 'Babaiee, Z., Hasani, R., Lechner, M., Rus, D., & Grosu, R. (2021). On-off
center-surround receptive fields for accurate and robust image classification.
In Proceedings of the 38th International Conference on Machine Learning
(Vol. 139, pp. 478–489). Virtual: ML Research Press.'
chicago: Babaiee, Zahra, Ramin Hasani, Mathias Lechner, Daniela Rus, and Radu Grosu.
“On-off Center-Surround Receptive Fields for Accurate and Robust Image Classification.”
In Proceedings of the 38th International Conference on Machine Learning,
139:478–89. ML Research Press, 2021.
ieee: Z. Babaiee, R. Hasani, M. Lechner, D. Rus, and R. Grosu, “On-off center-surround
receptive fields for accurate and robust image classification,” in Proceedings
of the 38th International Conference on Machine Learning, Virtual, 2021, vol.
139, pp. 478–489.
ista: 'Babaiee Z, Hasani R, Lechner M, Rus D, Grosu R. 2021. On-off center-surround
receptive fields for accurate and robust image classification. Proceedings of
the 38th International Conference on Machine Learning. ML: Machine Learning, PMLR,
vol. 139, 478–489.'
mla: Babaiee, Zahra, et al. “On-off Center-Surround Receptive Fields for Accurate
and Robust Image Classification.” Proceedings of the 38th International Conference
on Machine Learning, vol. 139, ML Research Press, 2021, pp. 478–89.
short: Z. Babaiee, R. Hasani, M. Lechner, D. Rus, R. Grosu, in:, Proceedings of
the 38th International Conference on Machine Learning, ML Research Press, 2021,
pp. 478–489.
conference:
end_date: 2021-07-24
location: Virtual
name: 'ML: Machine Learning'
start_date: 2021-07-18
date_created: 2022-01-25T15:46:33Z
date_published: 2021-07-01T00:00:00Z
date_updated: 2022-05-04T15:02:27Z
day: '01'
ddc:
- '000'
department:
- _id: GradSch
- _id: ToHe
file:
- access_level: open_access
checksum: d30eae62561bb517d9f978437d7677db
content_type: application/pdf
creator: mlechner
date_created: 2022-01-26T07:38:32Z
date_updated: 2022-01-26T07:38:32Z
file_id: '10681'
file_name: babaiee21a.pdf
file_size: 4246561
relation: main_file
success: 1
file_date_updated: 2022-01-26T07:38:32Z
has_accepted_license: '1'
intvolume: ' 139'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://proceedings.mlr.press/v139/babaiee21a
month: '07'
oa: 1
oa_version: Published Version
page: 478-489
project:
- _id: 25F42A32-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: Z211
name: The Wittgenstein Prize
publication: Proceedings of the 38th International Conference on Machine Learning
publication_identifier:
issn:
- 2640-3498
publication_status: published
publisher: ML Research Press
quality_controlled: '1'
status: public
title: On-off center-surround receptive fields for accurate and robust image classification
tmp:
image: /images/cc_by_nc_nd.png
legal_code_url: https://creativecommons.org/licenses/by-nc-nd/3.0/legalcode
name: Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND
3.0)
short: CC BY-NC-ND (3.0)
type: conference
user_id: 2EBD1598-F248-11E8-B48F-1D18A9856A87
volume: 139
year: '2021'
...
---
_id: '10669'
abstract:
- lang: eng
text: "We show that Neural ODEs, an emerging class of timecontinuous neural networks,
can be verified by solving a set of global-optimization problems. For this purpose,
we introduce Stochastic Lagrangian Reachability (SLR), an\r\nabstraction-based
technique for constructing a tight Reachtube (an over-approximation of the set
of reachable states\r\nover a given time-horizon), and provide stochastic guarantees
in the form of confidence intervals for the Reachtube bounds. SLR inherently avoids
the infamous wrapping effect (accumulation of over-approximation errors) by performing
local optimization steps to expand safe regions instead of repeatedly forward-propagating
them as is done by deterministic reachability methods. To enable fast local optimizations,
we introduce a novel forward-mode adjoint sensitivity method to compute gradients
without the need for backpropagation. Finally, we establish asymptotic and non-asymptotic
convergence rates for SLR."
acknowledgement: "The authors would like to thank the reviewers for their insightful
comments. RH and RG were partially supported by\r\nHorizon-2020 ECSEL Project grant
No. 783163 (iDev40). RH was partially supported by Boeing. ML was supported\r\nin
part by the Austrian Science Fund (FWF) under grant Z211-N23 (Wittgenstein Award).
SG was funded by FWF\r\nproject W1255-N23. JC was partially supported by NAWA Polish
Returns grant PPN/PPO/2018/1/00029. SS was supported by NSF awards DCL-2040599,
CCF-1918225, and CPS-1446832.\r\n"
alternative_title:
- Technical Tracks
article_processing_charge: No
arxiv: 1
author:
- first_name: Sophie
full_name: Grunbacher, Sophie
last_name: Grunbacher
- first_name: Ramin
full_name: Hasani, Ramin
last_name: Hasani
- first_name: Mathias
full_name: Lechner, Mathias
id: 3DC22916-F248-11E8-B48F-1D18A9856A87
last_name: Lechner
- first_name: Jacek
full_name: Cyranka, Jacek
last_name: Cyranka
- first_name: Scott A
full_name: Smolka, Scott A
last_name: Smolka
- first_name: Radu
full_name: Grosu, Radu
last_name: Grosu
citation:
ama: 'Grunbacher S, Hasani R, Lechner M, Cyranka J, Smolka SA, Grosu R. On the verification
of neural ODEs with stochastic guarantees. In: Proceedings of the AAAI Conference
on Artificial Intelligence. Vol 35. AAAI Press; 2021:11525-11535.'
apa: 'Grunbacher, S., Hasani, R., Lechner, M., Cyranka, J., Smolka, S. A., &
Grosu, R. (2021). On the verification of neural ODEs with stochastic guarantees.
In Proceedings of the AAAI Conference on Artificial Intelligence (Vol.
35, pp. 11525–11535). Virtual: AAAI Press.'
chicago: Grunbacher, Sophie, Ramin Hasani, Mathias Lechner, Jacek Cyranka, Scott
A Smolka, and Radu Grosu. “On the Verification of Neural ODEs with Stochastic
Guarantees.” In Proceedings of the AAAI Conference on Artificial Intelligence,
35:11525–35. AAAI Press, 2021.
ieee: S. Grunbacher, R. Hasani, M. Lechner, J. Cyranka, S. A. Smolka, and R. Grosu,
“On the verification of neural ODEs with stochastic guarantees,” in Proceedings
of the AAAI Conference on Artificial Intelligence, Virtual, 2021, vol. 35,
no. 13, pp. 11525–11535.
ista: 'Grunbacher S, Hasani R, Lechner M, Cyranka J, Smolka SA, Grosu R. 2021. On
the verification of neural ODEs with stochastic guarantees. Proceedings of the
AAAI Conference on Artificial Intelligence. AAAI: Association for the Advancement
of Artificial Intelligence, Technical Tracks, vol. 35, 11525–11535.'
mla: Grunbacher, Sophie, et al. “On the Verification of Neural ODEs with Stochastic
Guarantees.” Proceedings of the AAAI Conference on Artificial Intelligence,
vol. 35, no. 13, AAAI Press, 2021, pp. 11525–35.
short: S. Grunbacher, R. Hasani, M. Lechner, J. Cyranka, S.A. Smolka, R. Grosu,
in:, Proceedings of the AAAI Conference on Artificial Intelligence, AAAI Press,
2021, pp. 11525–11535.
conference:
end_date: 2021-02-09
location: Virtual
name: 'AAAI: Association for the Advancement of Artificial Intelligence'
start_date: 2021-02-02
date_created: 2022-01-25T15:47:20Z
date_published: 2021-05-28T00:00:00Z
date_updated: 2022-05-24T06:33:14Z
day: '28'
ddc:
- '000'
department:
- _id: GradSch
- _id: ToHe
external_id:
arxiv:
- '2012.08863'
file:
- access_level: open_access
checksum: 468d07041e282a1d46ffdae92f709630
content_type: application/pdf
creator: mlechner
date_created: 2022-01-26T07:38:08Z
date_updated: 2022-01-26T07:38:08Z
file_id: '10680'
file_name: 17372-Article Text-20866-1-2-20210518.pdf
file_size: 286906
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success: 1
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has_accepted_license: '1'
intvolume: ' 35'
issue: '13'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://ojs.aaai.org/index.php/AAAI/article/view/17372
month: '05'
oa: 1
oa_version: Published Version
page: 11525-11535
project:
- _id: 25F42A32-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: Z211
name: The Wittgenstein Prize
publication: Proceedings of the AAAI Conference on Artificial Intelligence
publication_identifier:
eissn:
- 2374-3468
isbn:
- 978-1-57735-866-4
issn:
- 2159-5399
publication_status: published
publisher: AAAI Press
quality_controlled: '1'
status: public
title: On the verification of neural ODEs with stochastic guarantees
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 35
year: '2021'
...
---
_id: '10670'
abstract:
- lang: eng
text: "Imitation learning enables high-fidelity, vision-based learning of policies
within rich, photorealistic environments. However, such techniques often rely
on traditional discrete-time neural models and face difficulties in generalizing
to domain shifts by failing to account for the causal relationships between the
agent and the environment. In this paper, we propose a theoretical and experimental
framework for learning causal representations using continuous-time neural networks,
specifically over their discrete-time counterparts. We evaluate our method in
the context of visual-control learning of drones over a series of complex tasks,
ranging from short- and long-term navigation, to chasing static and dynamic objects
through photorealistic environments. Our results demonstrate that causal continuous-time\r\ndeep
models can perform robust navigation tasks, where advanced recurrent models fail.
These models learn complex causal control representations directly from raw visual
inputs and scale to solve a variety of tasks using imitation learning."
acknowledgement: "C.V., R.H. A.A. and D.R. are partially supported by Boeing and MIT.
A.A. is supported by the National Science Foundation (NSF) Graduate Research Fellowship
Program. M.L. is supported in part by the Austrian Science Fund (FWF) under grant
Z211-N23 (Wittgenstein Award). Research was sponsored by the United States Air Force
Research Laboratory and the United States Air Force Artificial Intelligence Accelerator
and was accomplished under Cooperative Agreement Number FA8750-19-2-1000. The views
and conclusions contained in this document are those of the authors\r\nand should
not be interpreted as representing the official policies, either expressed or implied,
of the United States Air Force or the U.S. Government. The U.S. Government is authorized
to reproduce and distribute reprints for Government purposes notwithstanding any
copyright notation herein.\r\n"
alternative_title:
- ' Advances in Neural Information Processing Systems'
article_processing_charge: No
arxiv: 1
author:
- first_name: Charles J
full_name: Vorbach, Charles J
last_name: Vorbach
- first_name: Ramin
full_name: Hasani, Ramin
last_name: Hasani
- first_name: Alexander
full_name: Amini, Alexander
last_name: Amini
- first_name: Mathias
full_name: Lechner, Mathias
id: 3DC22916-F248-11E8-B48F-1D18A9856A87
last_name: Lechner
- first_name: Daniela
full_name: Rus, Daniela
last_name: Rus
citation:
ama: 'Vorbach CJ, Hasani R, Amini A, Lechner M, Rus D. Causal navigation by continuous-time
neural networks. In: 35th Conference on Neural Information Processing Systems.
; 2021.'
apa: Vorbach, C. J., Hasani, R., Amini, A., Lechner, M., & Rus, D. (2021). Causal
navigation by continuous-time neural networks. In 35th Conference on Neural
Information Processing Systems. Virtual.
chicago: Vorbach, Charles J, Ramin Hasani, Alexander Amini, Mathias Lechner, and
Daniela Rus. “Causal Navigation by Continuous-Time Neural Networks.” In 35th
Conference on Neural Information Processing Systems, 2021.
ieee: C. J. Vorbach, R. Hasani, A. Amini, M. Lechner, and D. Rus, “Causal navigation
by continuous-time neural networks,” in 35th Conference on Neural Information
Processing Systems, Virtual, 2021.
ista: 'Vorbach CJ, Hasani R, Amini A, Lechner M, Rus D. 2021. Causal navigation
by continuous-time neural networks. 35th Conference on Neural Information Processing
Systems. NeurIPS: Neural Information Processing Systems, Advances in Neural Information
Processing Systems, .'
mla: Vorbach, Charles J., et al. “Causal Navigation by Continuous-Time Neural Networks.”
35th Conference on Neural Information Processing Systems, 2021.
short: C.J. Vorbach, R. Hasani, A. Amini, M. Lechner, D. Rus, in:, 35th Conference
on Neural Information Processing Systems, 2021.
conference:
end_date: 2021-12-10
location: Virtual
name: 'NeurIPS: Neural Information Processing Systems'
start_date: 2021-12-06
date_created: 2022-01-25T15:47:50Z
date_published: 2021-12-01T00:00:00Z
date_updated: 2022-01-26T14:33:31Z
day: '01'
ddc:
- '000'
department:
- _id: GradSch
- _id: ToHe
external_id:
arxiv:
- '2106.08314'
file:
- access_level: open_access
checksum: be81f0ade174a8c9b2d4fe09590b2021
content_type: application/pdf
creator: mlechner
date_created: 2022-01-26T07:37:24Z
date_updated: 2022-01-26T07:37:24Z
file_id: '10679'
file_name: NeurIPS-2021-causal-navigation-by-continuous-time-neural-networks-Paper.pdf
file_size: 6841228
relation: main_file
success: 1
file_date_updated: 2022-01-26T07:37:24Z
has_accepted_license: '1'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://proceedings.neurips.cc/paper/2021/hash/67ba02d73c54f0b83c05507b7fb7267f-Abstract.html
month: '12'
oa: 1
oa_version: Published Version
project:
- _id: 25F42A32-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: Z211
name: The Wittgenstein Prize
publication: 35th Conference on Neural Information Processing Systems
publication_status: published
quality_controlled: '1'
status: public
title: Causal navigation by continuous-time neural networks
tmp:
image: /images/cc_by_nc_nd.png
legal_code_url: https://creativecommons.org/licenses/by-nc-nd/3.0/legalcode
name: Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND
3.0)
short: CC BY-NC-ND (3.0)
type: conference
user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9
year: '2021'
...
---
_id: '10671'
abstract:
- lang: eng
text: We introduce a new class of time-continuous recurrent neural network models.
Instead of declaring a learning system’s dynamics by implicit nonlinearities,
we construct networks of linear first-order dynamical systems modulated via nonlinear
interlinked gates. The resulting models represent dynamical systems with varying
(i.e., liquid) time-constants coupled to their hidden state, with outputs being
computed by numerical differential equation solvers. These neural networks exhibit
stable and bounded behavior, yield superior expressivity within the family of
neural ordinary differential equations, and give rise to improved performance
on time-series prediction tasks. To demonstrate these properties, we first take
a theoretical approach to find bounds over their dynamics, and compute their expressive
power by the trajectory length measure in a latent trajectory space. We then conduct
a series of time-series prediction experiments to manifest the approximation capability
of Liquid Time-Constant Networks (LTCs) compared to classical and modern RNNs.
acknowledgement: "R.H. and D.R. are partially supported by Boeing. R.H. and R.G. were
partially supported by the Horizon-2020 ECSEL\r\nProject grant No. 783163 (iDev40).
M.L. was supported in part by the Austrian Science Fund (FWF) under grant Z211-N23
(Wittgenstein Award). A.A. is supported by the National Science Foundation (NSF)
Graduate Research Fellowship Program. This research work is partially drawn from
the PhD dissertation of R.H."
alternative_title:
- Technical Tracks
article_processing_charge: No
arxiv: 1
author:
- first_name: Ramin
full_name: Hasani, Ramin
last_name: Hasani
- first_name: Mathias
full_name: Lechner, Mathias
id: 3DC22916-F248-11E8-B48F-1D18A9856A87
last_name: Lechner
- first_name: Alexander
full_name: Amini, Alexander
last_name: Amini
- first_name: Daniela
full_name: Rus, Daniela
last_name: Rus
- first_name: Radu
full_name: Grosu, Radu
last_name: Grosu
citation:
ama: 'Hasani R, Lechner M, Amini A, Rus D, Grosu R. Liquid time-constant networks.
In: Proceedings of the AAAI Conference on Artificial Intelligence. Vol
35. AAAI Press; 2021:7657-7666.'
apa: 'Hasani, R., Lechner, M., Amini, A., Rus, D., & Grosu, R. (2021). Liquid
time-constant networks. In Proceedings of the AAAI Conference on Artificial
Intelligence (Vol. 35, pp. 7657–7666). Virtual: AAAI Press.'
chicago: Hasani, Ramin, Mathias Lechner, Alexander Amini, Daniela Rus, and Radu
Grosu. “Liquid Time-Constant Networks.” In Proceedings of the AAAI Conference
on Artificial Intelligence, 35:7657–66. AAAI Press, 2021.
ieee: R. Hasani, M. Lechner, A. Amini, D. Rus, and R. Grosu, “Liquid time-constant
networks,” in Proceedings of the AAAI Conference on Artificial Intelligence,
Virtual, 2021, vol. 35, no. 9, pp. 7657–7666.
ista: 'Hasani R, Lechner M, Amini A, Rus D, Grosu R. 2021. Liquid time-constant
networks. Proceedings of the AAAI Conference on Artificial Intelligence. AAAI:
Association for the Advancement of Artificial Intelligence, Technical Tracks,
vol. 35, 7657–7666.'
mla: Hasani, Ramin, et al. “Liquid Time-Constant Networks.” Proceedings of the
AAAI Conference on Artificial Intelligence, vol. 35, no. 9, AAAI Press, 2021,
pp. 7657–66.
short: R. Hasani, M. Lechner, A. Amini, D. Rus, R. Grosu, in:, Proceedings of the
AAAI Conference on Artificial Intelligence, AAAI Press, 2021, pp. 7657–7666.
conference:
end_date: 2021-02-09
location: Virtual
name: 'AAAI: Association for the Advancement of Artificial Intelligence'
start_date: 2021-02-02
date_created: 2022-01-25T15:48:36Z
date_published: 2021-05-28T00:00:00Z
date_updated: 2022-05-24T06:36:54Z
day: '28'
ddc:
- '000'
department:
- _id: GradSch
- _id: ToHe
external_id:
arxiv:
- '2006.04439'
file:
- access_level: open_access
checksum: 0f06995fba06dbcfa7ed965fc66027ff
content_type: application/pdf
creator: mlechner
date_created: 2022-01-26T07:36:03Z
date_updated: 2022-01-26T07:36:03Z
file_id: '10678'
file_name: 16936-Article Text-20430-1-2-20210518 (1).pdf
file_size: 4302669
relation: main_file
success: 1
file_date_updated: 2022-01-26T07:36:03Z
has_accepted_license: '1'
intvolume: ' 35'
issue: '9'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://ojs.aaai.org/index.php/AAAI/article/view/16936
month: '05'
oa: 1
oa_version: Published Version
page: 7657-7666
project:
- _id: 25F42A32-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: Z211
name: The Wittgenstein Prize
publication: Proceedings of the AAAI Conference on Artificial Intelligence
publication_identifier:
eissn:
- 2374-3468
isbn:
- 978-1-57735-866-4
issn:
- 2159-5399
publication_status: published
publisher: AAAI Press
quality_controlled: '1'
status: public
title: Liquid time-constant networks
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 35
year: '2021'
...
---
_id: '10674'
abstract:
- lang: eng
text: 'In two-player games on graphs, the players move a token through a graph to
produce an infinite path, which determines the winner of the game. Such games
are central in formal methods since they model the interaction between a non-terminating
system and its environment. In bidding games the players bid for the right to
move the token: in each round, the players simultaneously submit bids, and the
higher bidder moves the token and pays the other player. Bidding games are known
to have a clean and elegant mathematical structure that relies on the ability
of the players to submit arbitrarily small bids. Many applications, however, require
a fixed granularity for the bids, which can represent, for example, the monetary
value expressed in cents. We study, for the first time, the combination of discrete-bidding
and infinite-duration games. Our most important result proves that these games
form a large determined subclass of concurrent games, where determinacy is the
strong property that there always exists exactly one player who can guarantee
winning the game. In particular, we show that, in contrast to non-discrete bidding
games, the mechanism with which tied bids are resolved plays an important role
in discrete-bidding games. We study several natural tie-breaking mechanisms and
show that, while some do not admit determinacy, most natural mechanisms imply
determinacy for every pair of initial budgets.'
acknowledgement: "This research was supported in part by the Austrian Science Fund
(FWF) under grants S11402-N23 (RiSE/SHiNE), Z211-N23 (Wittgenstein Award), and M
2369-N33 (Meitner fellowship).\r\n"
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Milad
full_name: Aghajohari, Milad
last_name: Aghajohari
- first_name: Guy
full_name: Avni, Guy
id: 463C8BC2-F248-11E8-B48F-1D18A9856A87
last_name: Avni
orcid: 0000-0001-5588-8287
- first_name: Thomas A
full_name: Henzinger, Thomas A
id: 40876CD8-F248-11E8-B48F-1D18A9856A87
last_name: Henzinger
orcid: 0000-0002-2985-7724
citation:
ama: Aghajohari M, Avni G, Henzinger TA. Determinacy in discrete-bidding infinite-duration
games. Logical Methods in Computer Science. 2021;17(1):10:1-10:23. doi:10.23638/LMCS-17(1:10)2021
apa: Aghajohari, M., Avni, G., & Henzinger, T. A. (2021). Determinacy in discrete-bidding
infinite-duration games. Logical Methods in Computer Science. International
Federation for Computational Logic. https://doi.org/10.23638/LMCS-17(1:10)2021
chicago: Aghajohari, Milad, Guy Avni, and Thomas A Henzinger. “Determinacy in Discrete-Bidding
Infinite-Duration Games.” Logical Methods in Computer Science. International
Federation for Computational Logic, 2021. https://doi.org/10.23638/LMCS-17(1:10)2021.
ieee: M. Aghajohari, G. Avni, and T. A. Henzinger, “Determinacy in discrete-bidding
infinite-duration games,” Logical Methods in Computer Science, vol. 17,
no. 1. International Federation for Computational Logic, p. 10:1-10:23, 2021.
ista: Aghajohari M, Avni G, Henzinger TA. 2021. Determinacy in discrete-bidding
infinite-duration games. Logical Methods in Computer Science. 17(1), 10:1-10:23.
mla: Aghajohari, Milad, et al. “Determinacy in Discrete-Bidding Infinite-Duration
Games.” Logical Methods in Computer Science, vol. 17, no. 1, International
Federation for Computational Logic, 2021, p. 10:1-10:23, doi:10.23638/LMCS-17(1:10)2021.
short: M. Aghajohari, G. Avni, T.A. Henzinger, Logical Methods in Computer Science
17 (2021) 10:1-10:23.
date_created: 2022-01-25T16:32:13Z
date_published: 2021-02-03T00:00:00Z
date_updated: 2023-08-17T06:56:42Z
day: '03'
ddc:
- '510'
department:
- _id: ToHe
doi: 10.23638/LMCS-17(1:10)2021
external_id:
arxiv:
- '1905.03588'
isi:
- '000658724600010'
file:
- access_level: open_access
checksum: b35586a50ed1ca8f44767de116d18d81
content_type: application/pdf
creator: alisjak
date_created: 2022-01-26T08:04:50Z
date_updated: 2022-01-26T08:04:50Z
file_id: '10690'
file_name: 2021_LMCS_AGHAJOHAR.pdf
file_size: 819878
relation: main_file
success: 1
file_date_updated: 2022-01-26T08:04:50Z
has_accepted_license: '1'
intvolume: ' 17'
isi: 1
issue: '1'
keyword:
- computer science
- computer science and game theory
- logic in computer science
language:
- iso: eng
month: '02'
oa: 1
oa_version: Published Version
page: 10:1-10:23
project:
- _id: 264B3912-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: M02369
name: Formal Methods meets Algorithmic Game Theory
- _id: 25F2ACDE-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: S11402-N23
name: Rigorous Systems Engineering
- _id: 25F42A32-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: Z211
name: The Wittgenstein Prize
publication: Logical Methods in Computer Science
publication_identifier:
eissn:
- 1860-5974
publication_status: published
publisher: International Federation for Computational Logic
quality_controlled: '1'
scopus_import: '1'
status: public
title: Determinacy in discrete-bidding infinite-duration games
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: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 17
year: '2021'
...
---
_id: '10688'
abstract:
- lang: eng
text: "Civl is a static verifier for concurrent programs designed around the conceptual
framework of layered refinement,\r\nwhich views the task of verifying a program
as a sequence of program simplification steps each justified by its own invariant.
Civl verifies a layered concurrent program that compactly expresses all the programs
in this sequence and the supporting invariants. This paper presents the design
and implementation of the Civl verifier."
acknowledgement: This research was performed while Bernhard Kragl was at IST Austria,
supported in part by the Austrian Science Fund (FWF) under grant Z211-N23 (Wittgenstein
Award).
alternative_title:
- Conference Series
article_processing_charge: No
author:
- first_name: Bernhard
full_name: Kragl, Bernhard
id: 320FC952-F248-11E8-B48F-1D18A9856A87
last_name: Kragl
orcid: 0000-0001-7745-9117
- first_name: Shaz
full_name: Qadeer, Shaz
last_name: Qadeer
citation:
ama: 'Kragl B, Qadeer S. The Civl verifier. In: Ruzica P, Whalen MW, eds. Proceedings
of the 21st Conference on Formal Methods in Computer-Aided Design. Vol 2.
TU Wien Academic Press; 2021:143–152. doi:10.34727/2021/isbn.978-3-85448-046-4_23'
apa: 'Kragl, B., & Qadeer, S. (2021). The Civl verifier. In P. Ruzica &
M. W. Whalen (Eds.), Proceedings of the 21st Conference on Formal Methods in
Computer-Aided Design (Vol. 2, pp. 143–152). Virtual: TU Wien Academic Press.
https://doi.org/10.34727/2021/isbn.978-3-85448-046-4_23'
chicago: Kragl, Bernhard, and Shaz Qadeer. “The Civl Verifier.” In Proceedings
of the 21st Conference on Formal Methods in Computer-Aided Design, edited
by Piskac Ruzica and Michael W. Whalen, 2:143–152. TU Wien Academic Press, 2021.
https://doi.org/10.34727/2021/isbn.978-3-85448-046-4_23.
ieee: B. Kragl and S. Qadeer, “The Civl verifier,” in Proceedings of the 21st
Conference on Formal Methods in Computer-Aided Design, Virtual, 2021, vol.
2, pp. 143–152.
ista: 'Kragl B, Qadeer S. 2021. The Civl verifier. Proceedings of the 21st Conference
on Formal Methods in Computer-Aided Design. FMCAD: Formal Methods in Computer-Aided
Design, Conference Series, vol. 2, 143–152.'
mla: Kragl, Bernhard, and Shaz Qadeer. “The Civl Verifier.” Proceedings of the
21st Conference on Formal Methods in Computer-Aided Design, edited by Piskac
Ruzica and Michael W. Whalen, vol. 2, TU Wien Academic Press, 2021, pp. 143–152,
doi:10.34727/2021/isbn.978-3-85448-046-4_23.
short: B. Kragl, S. Qadeer, in:, P. Ruzica, M.W. Whalen (Eds.), Proceedings of the
21st Conference on Formal Methods in Computer-Aided Design, TU Wien Academic Press,
2021, pp. 143–152.
conference:
end_date: 2021-10-22
location: Virtual
name: 'FMCAD: Formal Methods in Computer-Aided Design'
start_date: 2021-10-20
date_created: 2022-01-26T08:01:30Z
date_published: 2021-10-01T00:00:00Z
date_updated: 2022-01-26T08:20:41Z
day: '01'
ddc:
- '000'
department:
- _id: ToHe
doi: 10.34727/2021/isbn.978-3-85448-046-4_23
editor:
- first_name: Piskac
full_name: Ruzica, Piskac
last_name: Ruzica
- first_name: Michael W.
full_name: Whalen, Michael W.
last_name: Whalen
file:
- access_level: open_access
checksum: 35438ac9f9750340b7f8ae4ae3220d9f
content_type: application/pdf
creator: cchlebak
date_created: 2022-01-26T08:04:29Z
date_updated: 2022-01-26T08:04:29Z
file_id: '10689'
file_name: 2021_FCAD2021_Kragl.pdf
file_size: 390555
relation: main_file
success: 1
file_date_updated: 2022-01-26T08:04:29Z
has_accepted_license: '1'
intvolume: ' 2'
language:
- iso: eng
month: '10'
oa: 1
oa_version: Published Version
page: 143–152
project:
- _id: 25F42A32-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: Z211
name: The Wittgenstein Prize
publication: Proceedings of the 21st Conference on Formal Methods in Computer-Aided
Design
publication_identifier:
isbn:
- 978-3-85448-046-4
publication_status: published
publisher: TU Wien Academic Press
quality_controlled: '1'
status: public
title: The Civl verifier
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: 8b945eb4-e2f2-11eb-945a-df72226e66a9
volume: 2
year: '2021'
...
---
_id: '10694'
abstract:
- lang: eng
text: 'In a two-player zero-sum graph game the players move a token throughout a
graph to produce an infinite path, which determines the winner or payoff of the
game. Traditionally, the players alternate turns in moving the token. In bidding
games, however, the players have budgets, and in each turn, we hold an “auction”
(bidding) to determine which player moves the token: both players simultaneously
submit bids and the higher bidder moves the token. The bidding mechanisms differ
in their payment schemes. Bidding games were largely studied with variants of
first-price bidding in which only the higher bidder pays his bid. We focus on
all-pay bidding, where both players pay their bids. Finite-duration all-pay bidding
games were studied and shown to be technically more challenging than their first-price
counterparts. We study for the first time, infinite-duration all-pay bidding games.
Our most interesting results are for mean-payoff objectives: we portray a complete
picture for games played on strongly-connected graphs. We study both pure (deterministic)
and mixed (probabilistic) strategies and completely characterize the optimal and
almost-sure (with probability 1) payoffs the players can respectively guarantee.
We show that mean-payoff games under all-pay bidding exhibit the intriguing mathematical
properties of their first-price counterparts; namely, an equivalence with random-turn
games in which in each turn, the player who moves is selected according to a (biased)
coin toss. The equivalences for all-pay bidding are more intricate and unexpected
than for first-price bidding.'
acknowledgement: This research was supported in part by the Austrian Science Fund
(FWF) under grant Z211-N23 (Wittgenstein Award), ERC CoG 863818 (FoRM-SMArt), and
by 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: Guy
full_name: Avni, Guy
id: 463C8BC2-F248-11E8-B48F-1D18A9856A87
last_name: Avni
orcid: 0000-0001-5588-8287
- first_name: Ismael R
full_name: Jecker, Ismael R
id: 85D7C63E-7D5D-11E9-9C0F-98C4E5697425
last_name: Jecker
- 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, Jecker IR, Zikelic D. Infinite-duration all-pay bidding games. In:
Marx D, ed. Proceedings of the 2021 ACM-SIAM Symposium on Discrete Algorithms.
Society for Industrial and Applied Mathematics; 2021:617-636. doi:10.1137/1.9781611976465.38'
apa: 'Avni, G., Jecker, I. R., & Zikelic, D. (2021). Infinite-duration all-pay
bidding games. In D. Marx (Ed.), Proceedings of the 2021 ACM-SIAM Symposium
on Discrete Algorithms (pp. 617–636). Virtual: Society for Industrial and
Applied Mathematics. https://doi.org/10.1137/1.9781611976465.38'
chicago: Avni, Guy, Ismael R Jecker, and Dorde Zikelic. “Infinite-Duration All-Pay
Bidding Games.” In Proceedings of the 2021 ACM-SIAM Symposium on Discrete Algorithms,
edited by Dániel Marx, 617–36. Society for Industrial and Applied Mathematics,
2021. https://doi.org/10.1137/1.9781611976465.38.
ieee: G. Avni, I. R. Jecker, and D. Zikelic, “Infinite-duration all-pay bidding
games,” in Proceedings of the 2021 ACM-SIAM Symposium on Discrete Algorithms,
Virtual, 2021, pp. 617–636.
ista: 'Avni G, Jecker IR, Zikelic D. 2021. Infinite-duration all-pay bidding games.
Proceedings of the 2021 ACM-SIAM Symposium on Discrete Algorithms. SODA: Symposium
on Discrete Algorithms, 617–636.'
mla: Avni, Guy, et al. “Infinite-Duration All-Pay Bidding Games.” Proceedings
of the 2021 ACM-SIAM Symposium on Discrete Algorithms, edited by Dániel Marx,
Society for Industrial and Applied Mathematics, 2021, pp. 617–36, doi:10.1137/1.9781611976465.38.
short: G. Avni, I.R. Jecker, D. Zikelic, in:, D. Marx (Ed.), Proceedings of the
2021 ACM-SIAM Symposium on Discrete Algorithms, Society for Industrial and Applied
Mathematics, 2021, pp. 617–636.
conference:
end_date: 2021-01-13
location: Virtual
name: 'SODA: Symposium on Discrete Algorithms'
start_date: 2021-01-10
date_created: 2022-01-27T12:11:23Z
date_published: 2021-01-01T00:00:00Z
date_updated: 2025-07-14T09:10:12Z
day: '01'
department:
- _id: GradSch
- _id: KrCh
doi: 10.1137/1.9781611976465.38
ec_funded: 1
editor:
- first_name: Dániel
full_name: Marx, Dániel
last_name: Marx
external_id:
arxiv:
- '2005.06636'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2005.06636
month: '01'
oa: 1
oa_version: Preprint
page: 617-636
project:
- _id: 25F42A32-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: Z211
name: The Wittgenstein Prize
- _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 2021 ACM-SIAM Symposium on Discrete Algorithms
publication_identifier:
isbn:
- 978-1-61197-646-5
publication_status: published
publisher: Society for Industrial and Applied Mathematics
quality_controlled: '1'
scopus_import: '1'
status: public
title: Infinite-duration all-pay bidding games
type: conference
user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9
year: '2021'
...
---
_id: '10711'
abstract:
- lang: eng
text: In this paper, we investigate the distribution of the maximum of partial sums
of families of m -periodic complex-valued functions satisfying certain conditions.
We obtain precise uniform estimates for the distribution function of this maximum
in a near-optimal range. Our results apply to partial sums of Kloosterman sums
and other families of ℓ -adic trace functions, and are as strong as those obtained
by Bober, Goldmakher, Granville and Koukoulopoulos for character sums. In particular,
we improve on the recent work of the third author for Birch sums. However, unlike
character sums, we are able to construct families of m -periodic complex-valued
functions which satisfy our conditions, but for which the Pólya–Vinogradov inequality
is sharp.
acknowledgement: We would like to thank the anonymous referees for carefully reading
the paper and for their remarks and suggestions.
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Pascal
full_name: Autissier, Pascal
last_name: Autissier
- first_name: Dante
full_name: Bonolis, Dante
id: 6A459894-5FDD-11E9-AF35-BB24E6697425
last_name: Bonolis
- first_name: Youness
full_name: Lamzouri, Youness
last_name: Lamzouri
citation:
ama: Autissier P, Bonolis D, Lamzouri Y. The distribution of the maximum of partial
sums of Kloosterman sums and other trace functions. Compositio Mathematica.
2021;157(7):1610-1651. doi:10.1112/s0010437x21007351
apa: Autissier, P., Bonolis, D., & Lamzouri, Y. (2021). The distribution of
the maximum of partial sums of Kloosterman sums and other trace functions. Compositio
Mathematica. Cambridge University Press. https://doi.org/10.1112/s0010437x21007351
chicago: Autissier, Pascal, Dante Bonolis, and Youness Lamzouri. “The Distribution
of the Maximum of Partial Sums of Kloosterman Sums and Other Trace Functions.”
Compositio Mathematica. Cambridge University Press, 2021. https://doi.org/10.1112/s0010437x21007351.
ieee: P. Autissier, D. Bonolis, and Y. Lamzouri, “The distribution of the maximum
of partial sums of Kloosterman sums and other trace functions,” Compositio
Mathematica, vol. 157, no. 7. Cambridge University Press, pp. 1610–1651, 2021.
ista: Autissier P, Bonolis D, Lamzouri Y. 2021. The distribution of the maximum
of partial sums of Kloosterman sums and other trace functions. Compositio Mathematica.
157(7), 1610–1651.
mla: Autissier, Pascal, et al. “The Distribution of the Maximum of Partial Sums
of Kloosterman Sums and Other Trace Functions.” Compositio Mathematica,
vol. 157, no. 7, Cambridge University Press, 2021, pp. 1610–51, doi:10.1112/s0010437x21007351.
short: P. Autissier, D. Bonolis, Y. Lamzouri, Compositio Mathematica 157 (2021)
1610–1651.
date_created: 2022-02-01T08:10:43Z
date_published: 2021-06-28T00:00:00Z
date_updated: 2023-08-17T06:59:16Z
day: '28'
department:
- _id: TiBr
doi: 10.1112/s0010437x21007351
external_id:
arxiv:
- '1909.03266'
isi:
- '000667289300001'
intvolume: ' 157'
isi: 1
issue: '7'
keyword:
- Algebra and Number Theory
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1909.03266
month: '06'
oa: 1
oa_version: Preprint
page: 1610-1651
publication: Compositio Mathematica
publication_identifier:
eissn:
- 1570-5846
issn:
- 0010-437X
publication_status: published
publisher: Cambridge University Press
quality_controlled: '1'
status: public
title: The distribution of the maximum of partial sums of Kloosterman sums and other
trace functions
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 157
year: '2021'
...
---
_id: '10738'
abstract:
- lang: eng
text: We prove an adiabatic theorem for the Landau–Pekar equations. This allows
us to derive new results on the accuracy of their use as effective equations for
the time evolution generated by the Fröhlich Hamiltonian with large coupling constant
α. In particular, we show that the time evolution of Pekar product states with
coherent phonon field and the electron being trapped by the phonons is well approximated
by the Landau–Pekar equations until times short compared to α2.
acknowledgement: "N. L. and R. S. gratefully acknowledge financial support by the
European Research Council\r\n(ERC) under the European Union’s Horizon 2020 research
and innovation programme (grant\r\nagreement No 694227). B. S. acknowledges support
from the Swiss National Science Foundation (grant 200020_172623) and from the NCCR
SwissMAP. N. L. would like to thank\r\nAndreas Deuchert and David Mitrouskas for
interesting discussions. B. S. and R. S. would\r\nlike to thank Rupert Frank for
stimulating discussions about the time-evolution of a polaron.\r\n"
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Nikolai K
full_name: Leopold, Nikolai K
id: 4BC40BEC-F248-11E8-B48F-1D18A9856A87
last_name: Leopold
orcid: 0000-0002-0495-6822
- first_name: Simone Anna Elvira
full_name: Rademacher, Simone Anna Elvira
id: 856966FE-A408-11E9-977E-802DE6697425
last_name: Rademacher
orcid: 0000-0001-5059-4466
- first_name: Benjamin
full_name: Schlein, Benjamin
last_name: Schlein
- first_name: Robert
full_name: Seiringer, Robert
id: 4AFD0470-F248-11E8-B48F-1D18A9856A87
last_name: Seiringer
orcid: 0000-0002-6781-0521
citation:
ama: 'Leopold NK, Rademacher SAE, Schlein B, Seiringer R. The Landau–Pekar equations:
Adiabatic theorem and accuracy. Analysis and PDE. 2021;14(7):2079-2100.
doi:10.2140/APDE.2021.14.2079'
apa: 'Leopold, N. K., Rademacher, S. A. E., Schlein, B., & Seiringer, R. (2021). The
Landau–Pekar equations: Adiabatic theorem and accuracy. Analysis and PDE.
Mathematical Sciences Publishers. https://doi.org/10.2140/APDE.2021.14.2079'
chicago: 'Leopold, Nikolai K, Simone Anna Elvira Rademacher, Benjamin Schlein, and
Robert Seiringer. “ The Landau–Pekar Equations: Adiabatic Theorem and Accuracy.”
Analysis and PDE. Mathematical Sciences Publishers, 2021. https://doi.org/10.2140/APDE.2021.14.2079.'
ieee: 'N. K. Leopold, S. A. E. Rademacher, B. Schlein, and R. Seiringer, “ The Landau–Pekar
equations: Adiabatic theorem and accuracy,” Analysis and PDE, vol. 14,
no. 7. Mathematical Sciences Publishers, pp. 2079–2100, 2021.'
ista: 'Leopold NK, Rademacher SAE, Schlein B, Seiringer R. 2021. The Landau–Pekar
equations: Adiabatic theorem and accuracy. Analysis and PDE. 14(7), 2079–2100.'
mla: 'Leopold, Nikolai K., et al. “ The Landau–Pekar Equations: Adiabatic Theorem
and Accuracy.” Analysis and PDE, vol. 14, no. 7, Mathematical Sciences
Publishers, 2021, pp. 2079–100, doi:10.2140/APDE.2021.14.2079.'
short: N.K. Leopold, S.A.E. Rademacher, B. Schlein, R. Seiringer, Analysis and PDE
14 (2021) 2079–2100.
date_created: 2022-02-06T23:01:33Z
date_published: 2021-11-10T00:00:00Z
date_updated: 2023-10-17T11:26:45Z
day: '10'
department:
- _id: RoSe
doi: 10.2140/APDE.2021.14.2079
ec_funded: 1
external_id:
arxiv:
- '1904.12532'
isi:
- '000733976600004'
intvolume: ' 14'
isi: 1
issue: '7'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1904.12532
month: '11'
oa: 1
oa_version: Preprint
page: 2079-2100
project:
- _id: 25C6DC12-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '694227'
name: Analysis of quantum many-body systems
publication: Analysis and PDE
publication_identifier:
eissn:
- 1948-206X
issn:
- 2157-5045
publication_status: published
publisher: Mathematical Sciences Publishers
quality_controlled: '1'
scopus_import: '1'
status: public
title: ' The Landau–Pekar equations: Adiabatic theorem and accuracy'
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 14
year: '2021'
...
---
_id: '10762'
abstract:
- lang: eng
text: Methods inspired from machine learning have recently attracted great interest
in the computational study of quantum many-particle systems. So far, however,
it has proven challenging to deal with microscopic models in which the total number
of particles is not conserved. To address this issue, we propose a new variant
of neural network states, which we term neural coherent states. Taking the Fröhlich
impurity model as a case study, we show that neural coherent states can learn
the ground state of non-additive systems very well. In particular, we observe
substantial improvement over the standard coherent state estimates in the most
challenging intermediate coupling regime. Our approach is generic and does not
assume specific details of the system, suggesting wide applications.
acknowledgement: "We acknowledge fruitful discussions with Giacomo Bighin, Giammarco
Fabiani, Areg Ghazaryan, Christoph\r\nLampert, and Artem Volosniev at various stages
of this work. W.R. is a recipient of a DOC Fellowship of the\r\nAustrian Academy
of Sciences and has received funding from the EU Horizon 2020 programme under the
Marie\r\nSkłodowska-Curie Grant Agreement No. 665385. M. L. acknowledges support
by the European Research Council (ERC) Starting Grant No. 801770 (ANGULON). This
work is part of the Shell-NWO/FOM-initiative “Computational sciences for energy
research” of Shell and Chemical Sciences, Earth and Life Sciences, Physical Sciences,
FOM and STW."
article_processing_charge: No
arxiv: 1
author:
- first_name: Wojciech
full_name: Rzadkowski, Wojciech
id: 48C55298-F248-11E8-B48F-1D18A9856A87
last_name: Rzadkowski
orcid: 0000-0002-1106-4419
- first_name: Mikhail
full_name: Lemeshko, Mikhail
id: 37CB05FA-F248-11E8-B48F-1D18A9856A87
last_name: Lemeshko
orcid: 0000-0002-6990-7802
- first_name: Johan H.
full_name: Mentink, Johan H.
last_name: Mentink
citation:
ama: Rzadkowski W, Lemeshko M, Mentink JH. Artificial neural network states for
non-additive systems. arXiv. doi:10.48550/arXiv.2105.15193
apa: Rzadkowski, W., Lemeshko, M., & Mentink, J. H. (n.d.). Artificial neural
network states for non-additive systems. arXiv. https://doi.org/10.48550/arXiv.2105.15193
chicago: Rzadkowski, Wojciech, Mikhail Lemeshko, and Johan H. Mentink. “Artificial
Neural Network States for Non-Additive Systems.” ArXiv, n.d. https://doi.org/10.48550/arXiv.2105.15193.
ieee: W. Rzadkowski, M. Lemeshko, and J. H. Mentink, “Artificial neural network
states for non-additive systems,” arXiv. .
ista: Rzadkowski W, Lemeshko M, Mentink JH. Artificial neural network states for
non-additive systems. arXiv, 10.48550/arXiv.2105.15193.
mla: Rzadkowski, Wojciech, et al. “Artificial Neural Network States for Non-Additive
Systems.” ArXiv, doi:10.48550/arXiv.2105.15193.
short: W. Rzadkowski, M. Lemeshko, J.H. Mentink, ArXiv (n.d.).
date_created: 2022-02-17T11:18:57Z
date_published: 2021-05-31T00:00:00Z
date_updated: 2023-09-07T13:44:16Z
day: '31'
department:
- _id: MiLe
doi: 10.48550/arXiv.2105.15193
ec_funded: 1
external_id:
arxiv:
- '2105.15193'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2105.15193
month: '05'
oa: 1
oa_version: Preprint
page: '2105.15193'
project:
- _id: 2688CF98-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '801770'
name: 'Angulon: physics and applications of a new quasiparticle'
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '665385'
name: International IST Doctoral Program
publication: arXiv
publication_status: submitted
related_material:
record:
- id: '10759'
relation: dissertation_contains
status: public
status: public
title: Artificial neural network states for non-additive systems
type: preprint
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2021'
...
---
_id: '10803'
abstract:
- lang: eng
text: Given the abundance of applications of ranking in recent years, addressing
fairness concerns around automated ranking systems becomes necessary for increasing
the trust among end-users. Previous work on fair ranking has mostly focused on
application-specific fairness notions, often tailored to online advertising, and
it rarely considers learning as part of the process. In this work, we show how
to transfer numerous fairness notions from binary classification to a learning
to rank setting. Our formalism allows us to design methods for incorporating fairness
objectives with provable generalization guarantees. An extensive experimental
evaluation shows that our method can improve ranking fairness substantially with
no or only little loss of model quality.
article_number: '2102.05996'
article_processing_charge: No
arxiv: 1
author:
- first_name: Nikola H
full_name: Konstantinov, Nikola H
id: 4B9D76E4-F248-11E8-B48F-1D18A9856A87
last_name: Konstantinov
- first_name: Christoph
full_name: Lampert, Christoph
id: 40C20FD2-F248-11E8-B48F-1D18A9856A87
last_name: Lampert
orcid: 0000-0002-4561-241X
citation:
ama: Konstantinov NH, Lampert C. Fairness through regularization for learning to
rank. arXiv. doi:10.48550/arXiv.2102.05996
apa: Konstantinov, N. H., & Lampert, C. (n.d.). Fairness through regularization
for learning to rank. arXiv. https://doi.org/10.48550/arXiv.2102.05996
chicago: Konstantinov, Nikola H, and Christoph Lampert. “Fairness through Regularization
for Learning to Rank.” ArXiv, n.d. https://doi.org/10.48550/arXiv.2102.05996.
ieee: N. H. Konstantinov and C. Lampert, “Fairness through regularization for learning
to rank,” arXiv. .
ista: Konstantinov NH, Lampert C. Fairness through regularization for learning to
rank. arXiv, 2102.05996.
mla: Konstantinov, Nikola H., and Christoph Lampert. “Fairness through Regularization
for Learning to Rank.” ArXiv, 2102.05996, doi:10.48550/arXiv.2102.05996.
short: N.H. Konstantinov, C. Lampert, ArXiv (n.d.).
date_created: 2022-02-28T14:13:59Z
date_published: 2021-06-07T00:00:00Z
date_updated: 2023-09-07T13:42:08Z
day: '07'
department:
- _id: ChLa
doi: 10.48550/arXiv.2102.05996
external_id:
arxiv:
- '2102.05996'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2102.05996
month: '06'
oa: 1
oa_version: Preprint
publication: arXiv
publication_status: submitted
related_material:
record:
- id: '10799'
relation: dissertation_contains
status: public
status: public
title: Fairness through regularization for learning to rank
type: preprint
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2021'
...
---
_id: '10806'
abstract:
- lang: eng
text: Ligands are a fundamental part of nanocrystals. They control and direct nanocrystal
syntheses and provide colloidal stability. Bound ligands also affect the nanocrystals’
chemical reactivity and electronic structure. Surface chemistry is thus crucial
to understand nanocrystal properties and functionality. Here, we investigate the
synthesis of metal oxide nanocrystals (CeO2-x, ZnO, and NiO) from metal nitrate
precursors, in the presence of oleylamine ligands. Surprisingly, the nanocrystals
are capped exclusively with a fatty acid instead of oleylamine. Analysis of the
reaction mixtures with nuclear magnetic resonance spectroscopy revealed several
reaction byproducts and intermediates that are common to the decomposition of
Ce, Zn, Ni, and Zr nitrate precursors. Our evidence supports the oxidation of
alkylamine and formation of a carboxylic acid, thus unraveling this counterintuitive
surface chemistry.
acknowledgement: 'This work was financially supported by IST Austria and the Werner
Siemens Foundation. M.C. has received funding from the European Union’s Horizon
2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement
No. 665385. The work was also financially supported by University of Basel, SNSF
NCCR Molecular Systems Engineering (project number: 182895) and SNSF R’equip (project
number: 189622). J.L. is a Serra Húnter Fellow and is grateful to ICREA Academia
program and MICINN/FEDER RTI2018-093996-B-C31 and GC 2017 SGR 128 projects.'
article_processing_charge: Yes (via OA deal)
article_type: original
author:
- first_name: Mariano
full_name: Calcabrini, Mariano
id: 45D7531A-F248-11E8-B48F-1D18A9856A87
last_name: Calcabrini
- first_name: Dietger
full_name: Van den Eynden, Dietger
last_name: Van den Eynden
- first_name: Sergi
full_name: Sanchez Ribot, Sergi
id: ddae5a59-f6e0-11ea-865d-d9dc61e77a2a
last_name: Sanchez Ribot
- first_name: Rohan
full_name: Pokratath, Rohan
last_name: Pokratath
- first_name: Jordi
full_name: Llorca, Jordi
last_name: Llorca
- first_name: Jonathan
full_name: De Roo, Jonathan
last_name: De Roo
- first_name: Maria
full_name: Ibáñez, Maria
id: 43C61214-F248-11E8-B48F-1D18A9856A87
last_name: Ibáñez
orcid: 0000-0001-5013-2843
citation:
ama: 'Calcabrini M, Van den Eynden D, Sanchez Ribot S, et al. Ligand conversion
in nanocrystal synthesis: The oxidation of alkylamines to fatty acids by nitrate.
JACS Au. 2021;1(11):1898-1903. doi:10.1021/jacsau.1c00349'
apa: 'Calcabrini, M., Van den Eynden, D., Sanchez Ribot, S., Pokratath, R., Llorca,
J., De Roo, J., & Ibáñez, M. (2021). Ligand conversion in nanocrystal synthesis:
The oxidation of alkylamines to fatty acids by nitrate. JACS Au. American
Chemical Society. https://doi.org/10.1021/jacsau.1c00349'
chicago: 'Calcabrini, Mariano, Dietger Van den Eynden, Sergi Sanchez Ribot, Rohan
Pokratath, Jordi Llorca, Jonathan De Roo, and Maria Ibáñez. “Ligand Conversion
in Nanocrystal Synthesis: The Oxidation of Alkylamines to Fatty Acids by Nitrate.”
JACS Au. American Chemical Society, 2021. https://doi.org/10.1021/jacsau.1c00349.'
ieee: 'M. Calcabrini et al., “Ligand conversion in nanocrystal synthesis:
The oxidation of alkylamines to fatty acids by nitrate,” JACS Au, vol.
1, no. 11. American Chemical Society, pp. 1898–1903, 2021.'
ista: 'Calcabrini M, Van den Eynden D, Sanchez Ribot S, Pokratath R, Llorca J, De
Roo J, Ibáñez M. 2021. Ligand conversion in nanocrystal synthesis: The oxidation
of alkylamines to fatty acids by nitrate. JACS Au. 1(11), 1898–1903.'
mla: 'Calcabrini, Mariano, et al. “Ligand Conversion in Nanocrystal Synthesis: The
Oxidation of Alkylamines to Fatty Acids by Nitrate.” JACS Au, vol. 1, no.
11, American Chemical Society, 2021, pp. 1898–903, doi:10.1021/jacsau.1c00349.'
short: M. Calcabrini, D. Van den Eynden, S. Sanchez Ribot, R. Pokratath, J. Llorca,
J. De Roo, M. Ibáñez, JACS Au 1 (2021) 1898–1903.
date_created: 2022-03-02T15:24:16Z
date_published: 2021-11-22T00:00:00Z
date_updated: 2023-05-05T08:45:36Z
day: '22'
ddc:
- '540'
department:
- _id: MaIb
doi: 10.1021/jacsau.1c00349
ec_funded: 1
file:
- access_level: open_access
checksum: 1c66a35369e911312a359111420318a9
content_type: application/pdf
creator: cchlebak
date_created: 2022-03-02T15:33:18Z
date_updated: 2022-03-02T15:33:18Z
file_id: '10807'
file_name: 2021_JACSAu_Calcabrini.pdf
file_size: 1257973
relation: main_file
success: 1
file_date_updated: 2022-03-02T15:33:18Z
has_accepted_license: '1'
intvolume: ' 1'
issue: '11'
keyword:
- general medicine
language:
- iso: eng
month: '11'
oa: 1
oa_version: Published Version
page: 1898-1903
project:
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '665385'
name: International IST Doctoral Program
- _id: 9B8F7476-BA93-11EA-9121-9846C619BF3A
name: 'HighTE: The Werner Siemens Laboratory for the High Throughput Discovery of
Semiconductors for Waste Heat Recovery'
- _id: B67AFEDC-15C9-11EA-A837-991A96BB2854
name: IST Austria Open Access Fund
publication: JACS Au
publication_identifier:
eissn:
- 2691-3704
issn:
- 2691-3704
publication_status: published
publisher: American Chemical Society
quality_controlled: '1'
related_material:
link:
- relation: earlier_version
url: https://doi.org/10.26434/chemrxiv-2021-cn2fr
record:
- id: '12885'
relation: dissertation_contains
status: public
status: public
title: 'Ligand conversion in nanocrystal synthesis: The oxidation of alkylamines to
fatty acids by nitrate'
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: 8b945eb4-e2f2-11eb-945a-df72226e66a9
volume: 1
year: '2021'
...
---
_id: '10809'
abstract:
- lang: eng
text: Thermoelectric materials are engines that convert heat into an electrical
current. Intuitively, the efficiency of this process depends on how many electrons
(charge carriers) can move and how easily they do so, how much energy those moving
electrons transport, and how easily the temperature gradient is maintained. In
terms of material properties, an excellent thermoelectric material requires a
high electrical conductivity σ, a high Seebeck coefficient S (a measure of the
induced thermoelectric voltage as a function of temperature gradient), and a low
thermal conductivity κ. The challenge is that these three properties are strongly
interrelated in a conflicting manner (1). On page 722 of this issue, Roychowdhury
et al. (2) have found a way to partially break these ties in silver antimony telluride
(AgSbTe2) with the addition of cadmium (Cd) cations, which increase the ordering
in this inherently disordered thermoelectric material.
article_processing_charge: No
article_type: letter_note
author:
- first_name: Yu
full_name: Liu, Yu
id: 2A70014E-F248-11E8-B48F-1D18A9856A87
last_name: Liu
orcid: 0000-0001-7313-6740
- first_name: Maria
full_name: Ibáñez, Maria
id: 43C61214-F248-11E8-B48F-1D18A9856A87
last_name: Ibáñez
orcid: 0000-0001-5013-2843
citation:
ama: Liu Y, Ibáñez M. Tidying up the mess. Science. 2021;371(6530):678-679.
doi:10.1126/science.abg0886
apa: Liu, Y., & Ibáñez, M. (2021). Tidying up the mess. Science. American
Association for the Advancement of Science. https://doi.org/10.1126/science.abg0886
chicago: Liu, Yu, and Maria Ibáñez. “Tidying up the Mess.” Science. American
Association for the Advancement of Science, 2021. https://doi.org/10.1126/science.abg0886.
ieee: Y. Liu and M. Ibáñez, “Tidying up the mess,” Science, vol. 371, no.
6530. American Association for the Advancement of Science, pp. 678–679, 2021.
ista: Liu Y, Ibáñez M. 2021. Tidying up the mess. Science. 371(6530), 678–679.
mla: Liu, Yu, and Maria Ibáñez. “Tidying up the Mess.” Science, vol. 371,
no. 6530, American Association for the Advancement of Science, 2021, pp. 678–79,
doi:10.1126/science.abg0886.
short: Y. Liu, M. Ibáñez, Science 371 (2021) 678–679.
date_created: 2022-03-03T09:51:48Z
date_published: 2021-02-12T00:00:00Z
date_updated: 2023-08-17T07:00:35Z
day: '12'
department:
- _id: MaIb
doi: 10.1126/science.abg0886
external_id:
isi:
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pmid:
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intvolume: ' 371'
isi: 1
issue: '6530'
keyword:
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language:
- iso: eng
month: '02'
oa_version: None
page: 678-679
pmid: 1
publication: Science
publication_identifier:
eissn:
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issn:
- 0036-8075
publication_status: published
publisher: American Association for the Advancement of Science
quality_controlled: '1'
scopus_import: '1'
status: public
title: Tidying up the mess
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 371
year: '2021'
...
---
_id: '10816'
abstract:
- lang: eng
text: Pattern separation is a fundamental brain computation that converts small
differences in input patterns into large differences in output patterns. Several
synaptic mechanisms of pattern separation have been proposed, including code expansion,
inhibition and plasticity; however, which of these mechanisms play a role in the
entorhinal cortex (EC)–dentate gyrus (DG)–CA3 circuit, a classical pattern separation
circuit, remains unclear. Here we show that a biologically realistic, full-scale
EC–DG–CA3 circuit model, including granule cells (GCs) and parvalbumin-positive
inhibitory interneurons (PV+-INs) in the DG, is an efficient pattern separator.
Both external gamma-modulated inhibition and internal lateral inhibition mediated
by PV+-INs substantially contributed to pattern separation. Both local connectivity
and fast signaling at GC–PV+-IN synapses were important for maximum effectiveness.
Similarly, mossy fiber synapses with conditional detonator properties contributed
to pattern separation. By contrast, perforant path synapses with Hebbian synaptic
plasticity and direct EC–CA3 connection shifted the network towards pattern completion.
Our results demonstrate that the specific properties of cells and synapses optimize
higher-order computations in biological networks and might be useful to improve
the deep learning capabilities of technical networks.
acknowledged_ssus:
- _id: SSU
acknowledgement: We thank A. Aertsen, N. Kopell, W. Maass, A. Roth, F. Stella and
T. Vogels for critically reading earlier versions of the manuscript. We are grateful
to F. Marr and C. Altmutter for excellent technical assistance, E. Kralli-Beller
for manuscript editing, and the Scientific Service Units of IST Austria for efficient
support. Finally, we thank T. Carnevale, L. Erdös, M. Hines, D. Nykamp and D. Schröder
for useful discussions, and R. Friedrich and S. Wiechert for sharing unpublished
data. This project received funding from the European Research Council (ERC) under
the European Union’s Horizon 2020 research and innovation programme (grant agreement
no. 692692, P.J.) and the Fond zur Förderung der Wissenschaftlichen Forschung (Z
312-B27, Wittgenstein award to P.J. and P 31815 to S.J.G.).
article_processing_charge: No
article_type: original
author:
- first_name: José
full_name: Guzmán, José
id: 30CC5506-F248-11E8-B48F-1D18A9856A87
last_name: Guzmán
orcid: 0000-0003-2209-5242
- first_name: Alois
full_name: Schlögl, Alois
id: 45BF87EE-F248-11E8-B48F-1D18A9856A87
last_name: Schlögl
orcid: 0000-0002-5621-8100
- first_name: 'Claudia '
full_name: 'Espinoza Martinez, Claudia '
id: 31FFEE2E-F248-11E8-B48F-1D18A9856A87
last_name: Espinoza Martinez
orcid: 0000-0003-4710-2082
- first_name: Xiaomin
full_name: Zhang, Xiaomin
id: 423EC9C2-F248-11E8-B48F-1D18A9856A87
last_name: Zhang
- first_name: Benjamin
full_name: Suter, Benjamin
id: 4952F31E-F248-11E8-B48F-1D18A9856A87
last_name: Suter
orcid: 0000-0002-9885-6936
- first_name: Peter M
full_name: Jonas, Peter M
id: 353C1B58-F248-11E8-B48F-1D18A9856A87
last_name: Jonas
orcid: 0000-0001-5001-4804
citation:
ama: Guzmán J, Schlögl A, Espinoza Martinez C, Zhang X, Suter B, Jonas PM. How connectivity
rules and synaptic properties shape the efficacy of pattern separation in the
entorhinal cortex–dentate gyrus–CA3 network. Nature Computational Science.
2021;1(12):830-842. doi:10.1038/s43588-021-00157-1
apa: Guzmán, J., Schlögl, A., Espinoza Martinez, C., Zhang, X., Suter, B., &
Jonas, P. M. (2021). How connectivity rules and synaptic properties shape the
efficacy of pattern separation in the entorhinal cortex–dentate gyrus–CA3 network.
Nature Computational Science. Springer Nature. https://doi.org/10.1038/s43588-021-00157-1
chicago: Guzmán, José, Alois Schlögl, Claudia Espinoza Martinez, Xiaomin Zhang,
Benjamin Suter, and Peter M Jonas. “How Connectivity Rules and Synaptic Properties
Shape the Efficacy of Pattern Separation in the Entorhinal Cortex–Dentate Gyrus–CA3
Network.” Nature Computational Science. Springer Nature, 2021. https://doi.org/10.1038/s43588-021-00157-1.
ieee: J. Guzmán, A. Schlögl, C. Espinoza Martinez, X. Zhang, B. Suter, and P. M.
Jonas, “How connectivity rules and synaptic properties shape the efficacy of pattern
separation in the entorhinal cortex–dentate gyrus–CA3 network,” Nature Computational
Science, vol. 1, no. 12. Springer Nature, pp. 830–842, 2021.
ista: Guzmán J, Schlögl A, Espinoza Martinez C, Zhang X, Suter B, Jonas PM. 2021.
How connectivity rules and synaptic properties shape the efficacy of pattern separation
in the entorhinal cortex–dentate gyrus–CA3 network. Nature Computational Science.
1(12), 830–842.
mla: Guzmán, José, et al. “How Connectivity Rules and Synaptic Properties Shape
the Efficacy of Pattern Separation in the Entorhinal Cortex–Dentate Gyrus–CA3
Network.” Nature Computational Science, vol. 1, no. 12, Springer Nature,
2021, pp. 830–42, doi:10.1038/s43588-021-00157-1.
short: J. Guzmán, A. Schlögl, C. Espinoza Martinez, X. Zhang, B. Suter, P.M. Jonas,
Nature Computational Science 1 (2021) 830–842.
date_created: 2022-03-04T08:32:36Z
date_published: 2021-12-16T00:00:00Z
date_updated: 2023-08-10T22:30:10Z
day: '16'
ddc:
- '610'
department:
- _id: PeJo
doi: 10.1038/s43588-021-00157-1
ec_funded: 1
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intvolume: ' 1'
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keyword:
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language:
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project:
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call_identifier: H2020
grant_number: '692692'
name: Biophysics and circuit function of a giant cortical glumatergic synapse
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call_identifier: FWF
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title: How connectivity rules and synaptic properties shape the efficacy of pattern
separation in the entorhinal cortex–dentate gyrus–CA3 network
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...