---
_id: '12684'
abstract:
- lang: eng
text: Given a place ω of a global function field K over a finite field, with
associated affine function ring Rω and completion Kω , the aim of this paper
is to give an effective joint equidistribution result for renormalized primitive
lattice points (a,b)∈Rω2 in the plane Kω2 , and for renormalized solutions
to the gcd equation ax+by=1 . The main tools are techniques of Goronik and Nevo
for counting lattice points in well-rounded families of subsets. This gives a
sharper analog in positive characteristic of a result of Nevo and the first author
for the equidistribution of the primitive lattice points in \ZZ2 .
acknowledgement: "The authors warmly thank Amos Nevo for having presented the authors
to each other during\r\na beautiful conference in Goa in February 2016, where the
idea of this paper was born. The\r\nfirst author thanks the IHES for two post-doctoral
years when most of this paper was discussed,\r\nand the Topology team in Orsay for
financial support at the final stage. The first author was\r\nsupported by the EPRSC
EP/P026710/1 grant. Finally, we warmly thank the referee for many\r\nvery helpful
comments that have improved the readability of this paper."
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Tal
full_name: Horesh, Tal
id: C8B7BF48-8D81-11E9-BCA9-F536E6697425
last_name: Horesh
- first_name: Frédéric
full_name: Paulin, Frédéric
last_name: Paulin
citation:
ama: Horesh T, Paulin F. Effective equidistribution of lattice points in positive
characteristic. Journal de Theorie des Nombres de Bordeaux. 2022;34(3):679-703.
doi:10.5802/JTNB.1222
apa: Horesh, T., & Paulin, F. (2022). Effective equidistribution of lattice
points in positive characteristic. Journal de Theorie Des Nombres de Bordeaux.
Centre Mersenne. https://doi.org/10.5802/JTNB.1222
chicago: Horesh, Tal, and Frédéric Paulin. “Effective Equidistribution of Lattice
Points in Positive Characteristic.” Journal de Theorie Des Nombres de Bordeaux.
Centre Mersenne, 2022. https://doi.org/10.5802/JTNB.1222.
ieee: T. Horesh and F. Paulin, “Effective equidistribution of lattice points in
positive characteristic,” Journal de Theorie des Nombres de Bordeaux, vol.
34, no. 3. Centre Mersenne, pp. 679–703, 2022.
ista: Horesh T, Paulin F. 2022. Effective equidistribution of lattice points in
positive characteristic. Journal de Theorie des Nombres de Bordeaux. 34(3), 679–703.
mla: Horesh, Tal, and Frédéric Paulin. “Effective Equidistribution of Lattice Points
in Positive Characteristic.” Journal de Theorie Des Nombres de Bordeaux,
vol. 34, no. 3, Centre Mersenne, 2022, pp. 679–703, doi:10.5802/JTNB.1222.
short: T. Horesh, F. Paulin, Journal de Theorie Des Nombres de Bordeaux 34 (2022)
679–703.
date_created: 2023-02-26T23:01:02Z
date_published: 2022-01-27T00:00:00Z
date_updated: 2023-08-04T10:41:40Z
day: '27'
ddc:
- '510'
department:
- _id: TiBr
doi: 10.5802/JTNB.1222
external_id:
arxiv:
- '2001.01534'
isi:
- '000926504300003'
file:
- access_level: open_access
checksum: 08f28fded270251f568f610cf5166d69
content_type: application/pdf
creator: dernst
date_created: 2023-02-27T09:10:13Z
date_updated: 2023-02-27T09:10:13Z
file_id: '12689'
file_name: 2023_JourTheorieNombreBordeaux_Horesh.pdf
file_size: 870468
relation: main_file
success: 1
file_date_updated: 2023-02-27T09:10:13Z
has_accepted_license: '1'
intvolume: ' 34'
isi: 1
issue: '3'
language:
- iso: eng
license: https://creativecommons.org/licenses/by-nd/4.0/
month: '01'
oa: 1
oa_version: Published Version
page: 679-703
publication: Journal de Theorie des Nombres de Bordeaux
publication_identifier:
eissn:
- 2118-8572
issn:
- 1246-7405
publication_status: published
publisher: Centre Mersenne
quality_controlled: '1'
scopus_import: '1'
status: public
title: Effective equidistribution of lattice points in positive characteristic
tmp:
image: /image/cc_by_nd.png
legal_code_url: https://creativecommons.org/licenses/by-nd/4.0/legalcode
name: Creative Commons Attribution-NoDerivatives 4.0 International (CC BY-ND 4.0)
short: CC BY-ND (4.0)
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 34
year: '2022'
...
---
_id: '12750'
abstract:
- lang: eng
text: Quantum kinetically constrained models have recently attracted significant
attention due to their anomalous dynamics and thermalization. In this work, we
introduce a hitherto unexplored family of kinetically constrained models featuring
a conserved particle number and strong inversion-symmetry breaking due to facilitated
hopping. We demonstrate that these models provide a generic example of so-called
quantum Hilbert space fragmentation, that is manifested in disconnected sectors
in the Hilbert space that are not apparent in the computational basis. Quantum
Hilbert space fragmentation leads to an exponential in system size number of eigenstates
with exactly zero entanglement entropy across several bipartite cuts. These eigenstates
can be probed dynamically using quenches from simple initial product states. In
addition, we study the particle spreading under unitary dynamics launched from
the domain wall state, and find faster than diffusive dynamics at high particle
densities, that crosses over into logarithmically slow relaxation at smaller densities.
Using a classically simulable cellular automaton, we reproduce the logarithmic
dynamics observed in the quantum case. Our work suggests that particle conserving
constrained models with inversion symmetry breaking realize so far unexplored
universality classes of dynamics and invite their further theoretical and experimental
studies.
article_number: '2210.15607'
article_processing_charge: No
arxiv: 1
author:
- first_name: Pietro
full_name: Brighi, Pietro
id: 4115AF5C-F248-11E8-B48F-1D18A9856A87
last_name: Brighi
orcid: 0000-0002-7969-2729
- first_name: Marko
full_name: Ljubotina, Marko
id: F75EE9BE-5C90-11EA-905D-16643DDC885E
last_name: Ljubotina
orcid: 0000-0003-0038-7068
- first_name: Maksym
full_name: Serbyn, Maksym
id: 47809E7E-F248-11E8-B48F-1D18A9856A87
last_name: Serbyn
orcid: 0000-0002-2399-5827
citation:
ama: Brighi P, Ljubotina M, Serbyn M. Hilbert space fragmentation and slow dynamics
in particle-conserving quantum East models. arXiv. doi:10.48550/arXiv.2210.15607
apa: Brighi, P., Ljubotina, M., & Serbyn, M. (n.d.). Hilbert space fragmentation
and slow dynamics in particle-conserving quantum East models. arXiv. https://doi.org/10.48550/arXiv.2210.15607
chicago: Brighi, Pietro, Marko Ljubotina, and Maksym Serbyn. “Hilbert Space Fragmentation
and Slow Dynamics in Particle-Conserving Quantum East Models.” ArXiv, n.d.
https://doi.org/10.48550/arXiv.2210.15607.
ieee: P. Brighi, M. Ljubotina, and M. Serbyn, “Hilbert space fragmentation and slow
dynamics in particle-conserving quantum East models,” arXiv. .
ista: Brighi P, Ljubotina M, Serbyn M. Hilbert space fragmentation and slow dynamics
in particle-conserving quantum East models. arXiv, 2210.15607.
mla: Brighi, Pietro, et al. “Hilbert Space Fragmentation and Slow Dynamics in Particle-Conserving
Quantum East Models.” ArXiv, 2210.15607, doi:10.48550/arXiv.2210.15607.
short: P. Brighi, M. Ljubotina, M. Serbyn, ArXiv (n.d.).
date_created: 2023-03-23T14:33:13Z
date_published: 2022-11-07T00:00:00Z
date_updated: 2023-09-20T10:46:29Z
day: '07'
department:
- _id: GradSch
- _id: MaSe
doi: 10.48550/arXiv.2210.15607
external_id:
arxiv:
- '2210.15607'
language:
- iso: eng
license: https://creativecommons.org/licenses/by-nc-sa/4.0/
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2210.15607
month: '11'
oa: 1
oa_version: Preprint
publication: arXiv
publication_status: submitted
related_material:
record:
- id: '12732'
relation: dissertation_contains
status: public
- id: '14334'
relation: later_version
status: public
status: public
title: Hilbert space fragmentation and slow dynamics in particle-conserving quantum
East models
tmp:
image: /images/cc_by_nc_sa.png
legal_code_url: https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode
name: Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC
BY-NC-SA 4.0)
short: CC BY-NC-SA (4.0)
type: preprint
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2022'
...
---
_id: '12775'
abstract:
- lang: eng
text: "We consider the problem of approximating the reachability probabilities in
Markov decision processes (MDP) with uncountable (continuous) state and action
spaces. While there are algorithms that, for special classes of such MDP, provide
a sequence of approximations converging to the true value in the limit, our aim
is to obtain an algorithm with guarantees on the precision of the approximation.\r\nAs
this problem is undecidable in general, assumptions on the MDP are necessary.
Our main contribution is to identify sufficient assumptions that are as weak as
possible, thus approaching the \"boundary\" of which systems can be correctly
and reliably analyzed. To this end, we also argue why each of our assumptions
is necessary for algorithms based on processing finitely many observations.\r\nWe
present two solution variants. The first one provides converging lower bounds
under weaker assumptions than typical ones from previous works concerned with
guarantees. The second one then utilizes stronger assumptions to additionally
provide converging upper bounds. Altogether, we obtain an anytime algorithm, i.e.
yielding a sequence of approximants with known and iteratively improving precision,
converging to the true value in the limit. Besides, due to the generality of our
assumptions, our algorithms are very general templates, readily allowing for various
heuristics from literature in contrast to, e.g., a specific discretization algorithm.
Our theoretical contribution thus paves the way for future practical improvements
without sacrificing correctness guarantees."
acknowledgement: "Kush Grover: The author has been supported by the DFG research training
group GRK\r\n2428 ConVeY.\r\nMaximilian Weininger: The author has been partially
supported by DFG projects 383882557\r\nStatistical Unbounded Verification (SUV)
and 427755713 Group-By Objectives in Probabilistic\r\nVerification (GOPro)"
alternative_title:
- LIPIcs
article_number: '11'
article_processing_charge: No
arxiv: 1
author:
- first_name: Kush
full_name: Grover, Kush
last_name: Grover
- first_name: Jan
full_name: Kretinsky, Jan
id: 44CEF464-F248-11E8-B48F-1D18A9856A87
last_name: Kretinsky
orcid: 0000-0002-8122-2881
- first_name: Tobias
full_name: Meggendorfer, Tobias
id: b21b0c15-30a2-11eb-80dc-f13ca25802e1
last_name: Meggendorfer
orcid: 0000-0002-1712-2165
- first_name: Maimilian
full_name: Weininger, Maimilian
last_name: Weininger
citation:
ama: 'Grover K, Kretinsky J, Meggendorfer T, Weininger M. Anytime guarantees for
reachability in uncountable Markov decision processes. In: 33rd International
Conference on Concurrency Theory . Vol 243. Schloss Dagstuhl - Leibniz-Zentrum
für Informatik; 2022. doi:10.4230/LIPIcs.CONCUR.2022.11'
apa: 'Grover, K., Kretinsky, J., Meggendorfer, T., & Weininger, M. (2022). Anytime
guarantees for reachability in uncountable Markov decision processes. In 33rd
International Conference on Concurrency Theory (Vol. 243). Warsaw, Poland:
Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.CONCUR.2022.11'
chicago: Grover, Kush, Jan Kretinsky, Tobias Meggendorfer, and Maimilian Weininger.
“Anytime Guarantees for Reachability in Uncountable Markov Decision Processes.”
In 33rd International Conference on Concurrency Theory , Vol. 243. Schloss
Dagstuhl - Leibniz-Zentrum für Informatik, 2022. https://doi.org/10.4230/LIPIcs.CONCUR.2022.11.
ieee: K. Grover, J. Kretinsky, T. Meggendorfer, and M. Weininger, “Anytime guarantees
for reachability in uncountable Markov decision processes,” in 33rd International
Conference on Concurrency Theory , Warsaw, Poland, 2022, vol. 243.
ista: 'Grover K, Kretinsky J, Meggendorfer T, Weininger M. 2022. Anytime guarantees
for reachability in uncountable Markov decision processes. 33rd International
Conference on Concurrency Theory . CONCUR: Conference on Concurrency Theory, LIPIcs,
vol. 243, 11.'
mla: Grover, Kush, et al. “Anytime Guarantees for Reachability in Uncountable Markov
Decision Processes.” 33rd International Conference on Concurrency Theory ,
vol. 243, 11, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022, doi:10.4230/LIPIcs.CONCUR.2022.11.
short: K. Grover, J. Kretinsky, T. Meggendorfer, M. Weininger, in:, 33rd International
Conference on Concurrency Theory , Schloss Dagstuhl - Leibniz-Zentrum für Informatik,
2022.
conference:
end_date: 2022-09-16
location: Warsaw, Poland
name: 'CONCUR: Conference on Concurrency Theory'
start_date: 2022-09-13
date_created: 2023-03-28T08:09:32Z
date_published: 2022-09-15T00:00:00Z
date_updated: 2023-09-26T10:43:30Z
day: '15'
ddc:
- '000'
department:
- _id: KrCh
doi: 10.4230/LIPIcs.CONCUR.2022.11
external_id:
arxiv:
- '2008.04824'
file:
- access_level: open_access
checksum: e282e43d3ae0ba6e067b72f4583e13c0
content_type: application/pdf
creator: dernst
date_created: 2023-09-26T10:43:15Z
date_updated: 2023-09-26T10:43:15Z
file_id: '14372'
file_name: 2022_LIPIcS_Grover.pdf
file_size: 960036
relation: main_file
success: 1
file_date_updated: 2023-09-26T10:43:15Z
has_accepted_license: '1'
intvolume: ' 243'
language:
- iso: eng
license: https://creativecommons.org/licenses/by/4.0/
month: '09'
oa: 1
oa_version: Published Version
publication: '33rd International Conference on Concurrency Theory '
publication_identifier:
issn:
- 1868-8969
publication_status: published
publisher: Schloss Dagstuhl - Leibniz-Zentrum für Informatik
quality_controlled: '1'
scopus_import: '1'
status: public
title: Anytime guarantees for reachability in uncountable Markov decision processes
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 243
year: '2022'
...
---
_id: '12776'
abstract:
- lang: eng
text: An improved asymptotic formula is established for the number of rational points
of bounded height on the split smooth del Pezzo surface of degree 5. The proof
uses the five conic bundle structures on the surface.
acknowledgement: This work was begun while the author was participating in the programme
on "Diophantine equations" at the Hausdorff Research Institute for Mathematics in
Bonn in 2009. The hospitality and financial support of the institute is gratefully
acknowledged. The idea of using conic bundles to study the split del Pezzo surface
of degree 5 was explained to the author by Professor Salberger. The author is very
grateful to him for his input into this project and also to Shuntaro Yamagishi for
many useful comments on an earlier version of this manuscript. While working on
this paper the author was supported by FWF grant P32428-N35.
article_processing_charge: No
article_type: original
author:
- first_name: Timothy D
full_name: Browning, Timothy D
id: 35827D50-F248-11E8-B48F-1D18A9856A87
last_name: Browning
orcid: 0000-0002-8314-0177
citation:
ama: Browning TD. Revisiting the Manin–Peyre conjecture for the split del Pezzo
surface of degree 5. New York Journal of Mathematics. 2022;28:1193-1229.
apa: Browning, T. D. (2022). Revisiting the Manin–Peyre conjecture for the split
del Pezzo surface of degree 5. New York Journal of Mathematics. State University
of New York.
chicago: Browning, Timothy D. “Revisiting the Manin–Peyre Conjecture for the Split
Del Pezzo Surface of Degree 5.” New York Journal of Mathematics. State
University of New York, 2022.
ieee: T. D. Browning, “Revisiting the Manin–Peyre conjecture for the split del Pezzo
surface of degree 5,” New York Journal of Mathematics, vol. 28. State University
of New York, pp. 1193–1229, 2022.
ista: Browning TD. 2022. Revisiting the Manin–Peyre conjecture for the split del
Pezzo surface of degree 5. New York Journal of Mathematics. 28, 1193–1229.
mla: Browning, Timothy D. “Revisiting the Manin–Peyre Conjecture for the Split Del
Pezzo Surface of Degree 5.” New York Journal of Mathematics, vol. 28, State
University of New York, 2022, pp. 1193–229.
short: T.D. Browning, New York Journal of Mathematics 28 (2022) 1193–1229.
date_created: 2023-03-28T09:21:09Z
date_published: 2022-08-24T00:00:00Z
date_updated: 2023-10-18T07:59:13Z
day: '24'
ddc:
- '510'
department:
- _id: TiBr
file:
- access_level: open_access
checksum: c01e8291794a1bdb7416aa103cb68ef8
content_type: application/pdf
creator: dernst
date_created: 2023-03-30T07:09:35Z
date_updated: 2023-03-30T07:09:35Z
file_id: '12778'
file_name: 2022_NYJM_Browning.pdf
file_size: 897267
relation: main_file
success: 1
file_date_updated: 2023-03-30T07:09:35Z
has_accepted_license: '1'
intvolume: ' 28'
language:
- iso: eng
month: '08'
oa: 1
oa_version: Published Version
page: 1193 - 1229
project:
- _id: 26AEDAB2-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P32428
name: New frontiers of the Manin conjecture
publication: New York Journal of Mathematics
publication_identifier:
issn:
- 1076-9803
publication_status: published
publisher: State University of New York
quality_controlled: '1'
status: public
title: Revisiting the Manin–Peyre conjecture for the split del Pezzo surface of degree
5
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 28
year: '2022'
...
---
_id: '12780'
abstract:
- lang: eng
text: "The ability to scale out training workloads has been one of the key performance
enablers of deep learning. The main scaling approach is data-parallel GPU-based
training, which has been boosted by hardware and software support for highly efficient
point-to-point communication, and in particular via hardware bandwidth over-provisioning.
Overprovisioning comes at a cost: there is an order of magnitude price difference
between \"cloud-grade\" servers with such support, relative to their popular \"consumer-grade\"
counterparts, although single server-grade and consumer-grade GPUs can have similar
computational envelopes.\r\n\r\nIn this paper, we show that the costly hardware
overprovisioning approach can be supplanted via algorithmic and system design,
and propose a framework called CGX, which provides efficient software support
for compressed communication in ML applications, for both multi-GPU single-node
training, as well as larger-scale multi-node training. CGX is based on two technical
advances: At the system level, it relies on a re-developed communication stack
for ML frameworks, which provides flexible, highly-efficient support for compressed
communication. At the application level, it provides seamless, parameter-free
integration with popular frameworks, so that end-users do not have to modify training
recipes, nor significant training code. This is complemented by a layer-wise adaptive
compression technique which dynamically balances compression gains with accuracy
preservation. CGX integrates with popular ML frameworks, providing up to 3X speedups
for multi-GPU nodes based on commodity hardware, and order-of-magnitude improvements
in the multi-node setting, with negligible impact on accuracy."
acknowledgement: The authors sincerely thank Nikoli Dryden, Tal Ben-Nun, Torsten Hoefler
and Bapi Chatterjee for useful discussions throughout the development of this project.
article_processing_charge: Yes (via OA deal)
arxiv: 1
author:
- first_name: Ilia
full_name: Markov, Ilia
id: D0CF4148-C985-11E9-8066-0BDEE5697425
last_name: Markov
- first_name: Hamidreza
full_name: Ramezanikebrya, Hamidreza
last_name: Ramezanikebrya
- first_name: Dan-Adrian
full_name: Alistarh, Dan-Adrian
id: 4A899BFC-F248-11E8-B48F-1D18A9856A87
last_name: Alistarh
orcid: 0000-0003-3650-940X
citation:
ama: 'Markov I, Ramezanikebrya H, Alistarh D-A. CGX: Adaptive system support for
communication-efficient deep learning. In: Proceedings of the 23rd ACM/IFIP
International Middleware Conference. Association for Computing Machinery;
2022:241-254. doi:10.1145/3528535.3565248'
apa: 'Markov, I., Ramezanikebrya, H., & Alistarh, D.-A. (2022). CGX: Adaptive
system support for communication-efficient deep learning. In Proceedings of
the 23rd ACM/IFIP International Middleware Conference (pp. 241–254). Quebec,
QC, Canada: Association for Computing Machinery. https://doi.org/10.1145/3528535.3565248'
chicago: 'Markov, Ilia, Hamidreza Ramezanikebrya, and Dan-Adrian Alistarh. “CGX:
Adaptive System Support for Communication-Efficient Deep Learning.” In Proceedings
of the 23rd ACM/IFIP International Middleware Conference, 241–54. Association
for Computing Machinery, 2022. https://doi.org/10.1145/3528535.3565248.'
ieee: 'I. Markov, H. Ramezanikebrya, and D.-A. Alistarh, “CGX: Adaptive system support
for communication-efficient deep learning,” in Proceedings of the 23rd ACM/IFIP
International Middleware Conference, Quebec, QC, Canada, 2022, pp. 241–254.'
ista: 'Markov I, Ramezanikebrya H, Alistarh D-A. 2022. CGX: Adaptive system support
for communication-efficient deep learning. Proceedings of the 23rd ACM/IFIP International
Middleware Conference. Middleware: International Middleware Conference, 241–254.'
mla: 'Markov, Ilia, et al. “CGX: Adaptive System Support for Communication-Efficient
Deep Learning.” Proceedings of the 23rd ACM/IFIP International Middleware Conference,
Association for Computing Machinery, 2022, pp. 241–54, doi:10.1145/3528535.3565248.'
short: I. Markov, H. Ramezanikebrya, D.-A. Alistarh, in:, Proceedings of the 23rd
ACM/IFIP International Middleware Conference, Association for Computing Machinery,
2022, pp. 241–254.
conference:
end_date: 2022-11-11
location: Quebec, QC, Canada
name: 'Middleware: International Middleware Conference'
start_date: 2022-11-07
date_created: 2023-03-31T06:17:00Z
date_published: 2022-11-01T00:00:00Z
date_updated: 2023-04-03T06:21:04Z
day: '01'
ddc:
- '000'
department:
- _id: DaAl
doi: 10.1145/3528535.3565248
external_id:
arxiv:
- '2111.08617'
file:
- access_level: open_access
checksum: 1a397746235f245da5468819247ff663
content_type: application/pdf
creator: dernst
date_created: 2023-04-03T06:17:58Z
date_updated: 2023-04-03T06:17:58Z
file_id: '12795'
file_name: 2022_ACMMiddleware_Markov.pdf
file_size: 1514169
relation: main_file
success: 1
file_date_updated: 2023-04-03T06:17:58Z
has_accepted_license: '1'
language:
- iso: eng
month: '11'
oa: 1
oa_version: Published Version
page: 241-254
publication: Proceedings of the 23rd ACM/IFIP International Middleware Conference
publication_identifier:
isbn:
- '9781450393409'
publication_status: published
publisher: Association for Computing Machinery
quality_controlled: '1'
status: public
title: 'CGX: Adaptive system support for communication-efficient deep learning'
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2022'
...
---
_id: '12793'
abstract:
- lang: eng
text: "Let F be a global function field with constant field Fq. Let G be a reductive
group over Fq. We establish a variant of Arthur's truncated kernel for G and for
its Lie algebra which generalizes Arthur's original construction. We establish
a coarse geometric expansion for our variant truncation.\r\nAs applications, we
consider some existence and uniqueness problems of some cuspidal automorphic representations
for the functions field of the projective line P1Fq with two points of ramifications."
acknowledgement: 'I’d like to thank Prof. Chaudouard for introducing me to this area.
I’d like to thank Prof. Harris for asking me the question that makes Section 10
possible. I’m grateful for the support of Prof. Hausel and IST Austria. The author
was funded by an ISTplus fellowship: This project has received funding from the
European Union’s Horizon 2020 research and innovation programme under the Marie
Skłodowska-Curie Grant Agreement No. 754411.'
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Hongjie
full_name: Yu, Hongjie
id: 3D7DD9BE-F248-11E8-B48F-1D18A9856A87
last_name: Yu
orcid: 0000-0001-5128-7126
citation:
ama: Yu H. A coarse geometric expansion of a variant of Arthur’s truncated traces
and some applications. Pacific Journal of Mathematics. 2022;321(1):193-237.
doi:10.2140/pjm.2022.321.193
apa: Yu, H. (2022). A coarse geometric expansion of a variant of Arthur’s truncated
traces and some applications. Pacific Journal of Mathematics. Mathematical
Sciences Publishers. https://doi.org/10.2140/pjm.2022.321.193
chicago: Yu, Hongjie. “ A Coarse Geometric Expansion of a Variant of Arthur’s Truncated
Traces and Some Applications.” Pacific Journal of Mathematics. Mathematical
Sciences Publishers, 2022. https://doi.org/10.2140/pjm.2022.321.193.
ieee: H. Yu, “ A coarse geometric expansion of a variant of Arthur’s truncated traces
and some applications,” Pacific Journal of Mathematics, vol. 321, no. 1.
Mathematical Sciences Publishers, pp. 193–237, 2022.
ista: Yu H. 2022. A coarse geometric expansion of a variant of Arthur’s truncated
traces and some applications. Pacific Journal of Mathematics. 321(1), 193–237.
mla: Yu, Hongjie. “ A Coarse Geometric Expansion of a Variant of Arthur’s Truncated
Traces and Some Applications.” Pacific Journal of Mathematics, vol. 321,
no. 1, Mathematical Sciences Publishers, 2022, pp. 193–237, doi:10.2140/pjm.2022.321.193.
short: H. Yu, Pacific Journal of Mathematics 321 (2022) 193–237.
date_created: 2023-04-02T22:01:11Z
date_published: 2022-08-29T00:00:00Z
date_updated: 2023-08-04T10:42:38Z
day: '29'
department:
- _id: TaHa
doi: 10.2140/pjm.2022.321.193
ec_funded: 1
external_id:
arxiv:
- '2109.10245'
isi:
- '000954466300006'
intvolume: ' 321'
isi: 1
issue: '1'
keyword:
- Arthur–Selberg trace formula
- cuspidal automorphic representations
- global function fields
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2109.10245
month: '08'
oa: 1
oa_version: Preprint
page: 193-237
project:
- _id: 260C2330-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '754411'
name: ISTplus - Postdoctoral Fellowships
publication: Pacific Journal of Mathematics
publication_identifier:
eissn:
- 1945-5844
issn:
- 0030-8730
publication_status: published
publisher: Mathematical Sciences Publishers
quality_controlled: '1'
scopus_import: '1'
status: public
title: ' A coarse geometric expansion of a variant of Arthur''s truncated traces and
some applications'
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 321
year: '2022'
...
---
_id: '12860'
abstract:
- lang: eng
text: 'Memorization of the relation between entities in a dataset can lead to privacy
issues when using a trained model for question answering. We introduce Relational
Memorization (RM) to understand, quantify and control this phenomenon. While bounding
general memorization can have detrimental effects on the performance of a trained
model, bounding RM does not prevent effective learning. The difference is most
pronounced when the data distribution is long-tailed, with many queries having
only few training examples: Impeding general memorization prevents effective learning,
while impeding only relational memorization still allows learning general properties
of the underlying concepts. We formalize the notion of Relational Privacy (RP)
and, inspired by Differential Privacy (DP), we provide a possible definition of
Differential Relational Privacy (DrP). These notions can be used to describe and
compute bounds on the amount of RM in a trained model. We illustrate Relational
Privacy concepts in experiments with large-scale models for Question Answering.'
article_number: '2203.16701'
article_processing_charge: No
arxiv: 1
author:
- first_name: Simone
full_name: Bombari, Simone
id: ca726dda-de17-11ea-bc14-f9da834f63aa
last_name: Bombari
- first_name: Alessandro
full_name: Achille, Alessandro
last_name: Achille
- first_name: Zijian
full_name: Wang, Zijian
last_name: Wang
- first_name: Yu-Xiang
full_name: Wang, Yu-Xiang
last_name: Wang
- first_name: Yusheng
full_name: Xie, Yusheng
last_name: Xie
- first_name: Kunwar Yashraj
full_name: Singh, Kunwar Yashraj
last_name: Singh
- first_name: Srikar
full_name: Appalaraju, Srikar
last_name: Appalaraju
- first_name: Vijay
full_name: Mahadevan, Vijay
last_name: Mahadevan
- first_name: Stefano
full_name: Soatto, Stefano
last_name: Soatto
citation:
ama: Bombari S, Achille A, Wang Z, et al. Towards differential relational privacy
and its use in question answering. arXiv. doi:10.48550/arXiv.2203.16701
apa: Bombari, S., Achille, A., Wang, Z., Wang, Y.-X., Xie, Y., Singh, K. Y., … Soatto,
S. (n.d.). Towards differential relational privacy and its use in question answering.
arXiv. https://doi.org/10.48550/arXiv.2203.16701
chicago: Bombari, Simone, Alessandro Achille, Zijian Wang, Yu-Xiang Wang, Yusheng
Xie, Kunwar Yashraj Singh, Srikar Appalaraju, Vijay Mahadevan, and Stefano Soatto.
“Towards Differential Relational Privacy and Its Use in Question Answering.” ArXiv,
n.d. https://doi.org/10.48550/arXiv.2203.16701.
ieee: S. Bombari et al., “Towards differential relational privacy and its
use in question answering,” arXiv. .
ista: Bombari S, Achille A, Wang Z, Wang Y-X, Xie Y, Singh KY, Appalaraju S, Mahadevan
V, Soatto S. Towards differential relational privacy and its use in question answering.
arXiv, 2203.16701.
mla: Bombari, Simone, et al. “Towards Differential Relational Privacy and Its Use
in Question Answering.” ArXiv, 2203.16701, doi:10.48550/arXiv.2203.16701.
short: S. Bombari, A. Achille, Z. Wang, Y.-X. Wang, Y. Xie, K.Y. Singh, S. Appalaraju,
V. Mahadevan, S. Soatto, ArXiv (n.d.).
date_created: 2023-04-23T16:11:48Z
date_published: 2022-03-30T00:00:00Z
date_updated: 2023-04-25T07:34:49Z
day: '30'
department:
- _id: GradSch
- _id: MaMo
doi: 10.48550/arXiv.2203.16701
external_id:
arxiv:
- '2203.16701'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2203.16701
month: '03'
oa: 1
oa_version: Preprint
publication: arXiv
publication_status: submitted
status: public
title: Towards differential relational privacy and its use in question answering
type: preprint
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2022'
...
---
_id: '12894'
acknowledgement: "The abstracts in this booklet are licenced under a CC BY 4.0 licence
(https://creativecommons.org/licenses/by/4.0/legalcode), except Markus Wallerberger’s
contribution at page 21, licenced under a CC BY-SA 4.0 licence (https://creativecommons.org/licenses/by-sa/4.0/legalcode).\r\n"
article_processing_charge: No
author:
- first_name: Alois
full_name: Schlögl, Alois
id: 45BF87EE-F248-11E8-B48F-1D18A9856A87
last_name: Schlögl
orcid: 0000-0002-5621-8100
- first_name: Andrei
full_name: Hornoiu, Andrei
id: 77129392-B450-11EA-8745-D4653DDC885E
last_name: Hornoiu
- first_name: Stefano
full_name: Elefante, Stefano
id: 490F40CE-F248-11E8-B48F-1D18A9856A87
last_name: Elefante
- first_name: Stephan
full_name: Stadlbauer, Stephan
id: 4D0BC184-F248-11E8-B48F-1D18A9856A87
last_name: Stadlbauer
citation:
ama: 'Schlögl A, Hornoiu A, Elefante S, Stadlbauer S. Where is the sweet spot? A
procurement story of general purpose compute nodes. In: ASHPC22 - Austrian-Slovenian
HPC Meeting 2022. EuroCC Austria c/o Universität Wien; 2022:7. doi:10.25365/phaidra.337'
apa: 'Schlögl, A., Hornoiu, A., Elefante, S., & Stadlbauer, S. (2022). Where
is the sweet spot? A procurement story of general purpose compute nodes. In ASHPC22
- Austrian-Slovenian HPC Meeting 2022 (p. 7). Grundlsee, Austria: EuroCC Austria
c/o Universität Wien. https://doi.org/10.25365/phaidra.337'
chicago: Schlögl, Alois, Andrei Hornoiu, Stefano Elefante, and Stephan Stadlbauer.
“Where Is the Sweet Spot? A Procurement Story of General Purpose Compute Nodes.”
In ASHPC22 - Austrian-Slovenian HPC Meeting 2022, 7. EuroCC Austria c/o
Universität Wien, 2022. https://doi.org/10.25365/phaidra.337.
ieee: A. Schlögl, A. Hornoiu, S. Elefante, and S. Stadlbauer, “Where is the sweet
spot? A procurement story of general purpose compute nodes,” in ASHPC22 - Austrian-Slovenian
HPC Meeting 2022, Grundlsee, Austria, 2022, p. 7.
ista: 'Schlögl A, Hornoiu A, Elefante S, Stadlbauer S. 2022. Where is the sweet
spot? A procurement story of general purpose compute nodes. ASHPC22 - Austrian-Slovenian
HPC Meeting 2022. ASHPC: Austrian-Slovenian HPC Meeting, 7.'
mla: Schlögl, Alois, et al. “Where Is the Sweet Spot? A Procurement Story of General
Purpose Compute Nodes.” ASHPC22 - Austrian-Slovenian HPC Meeting 2022,
EuroCC Austria c/o Universität Wien, 2022, p. 7, doi:10.25365/phaidra.337.
short: A. Schlögl, A. Hornoiu, S. Elefante, S. Stadlbauer, in:, ASHPC22 - Austrian-Slovenian
HPC Meeting 2022, EuroCC Austria c/o Universität Wien, 2022, p. 7.
conference:
end_date: 2022-06-02
location: Grundlsee, Austria
name: 'ASHPC: Austrian-Slovenian HPC Meeting'
start_date: 2022-05-31
date_created: 2023-05-05T09:13:42Z
date_published: 2022-06-02T00:00:00Z
date_updated: 2023-05-16T07:42:56Z
day: '02'
ddc:
- '000'
department:
- _id: ScienComp
doi: 10.25365/phaidra.337
file:
- access_level: open_access
checksum: e3f8c240b85422ce2190e7b203cc2563
content_type: application/pdf
creator: schloegl
date_created: 2023-05-05T09:06:00Z
date_updated: 2023-05-05T09:06:00Z
file_id: '12895'
file_name: BOOKLET_ASHPC22.pdf
file_size: 7180531
relation: main_file
success: 1
file_date_updated: 2023-05-05T09:06:00Z
has_accepted_license: '1'
language:
- iso: eng
month: '06'
oa: 1
oa_version: Published Version
page: '7'
publication: ASHPC22 - Austrian-Slovenian HPC Meeting 2022
publication_identifier:
isbn:
- 978-3-200-08499-5
publication_status: published
publisher: EuroCC Austria c/o Universität Wien
status: public
title: Where is the sweet spot? A procurement story of general purpose compute 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: conference_abstract
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2022'
...
---
_id: '12923'
abstract:
- lang: eng
text: Photoredox-mediated Ni-catalyzed cross-couplings are powerful transformations
to form carbon–heteroatom bonds and are generally photocatalyzed by noble metal
complexes. Low-cost and easy-to-prepare carbon dots (CDs) are attractive quasi-homogeneous
photocatalyst alternatives, but their applicability is limited by their short
photoluminescence (PL) lifetimes. By tuning the surface and PL properties of CDs,
we designed colloidal CD nano-photocatalysts for a broad range of Ni-mediated
cross-couplings between aryl halides and nucleophiles. In particular, a CD decorated
with amino groups permitted coupling to a wide range of aryl halides and thiols
under mild, base-free conditions. Mechanistic studies suggested dynamic quenching
of the CD excited state by the Ni co-catalyst and identified that pyridinium iodide
(pyHI), a previously used additive in metallaphotocatalyzed cross-couplings, can
also act as a photocatalyst in such transformations.
article_processing_charge: No
article_type: original
author:
- first_name: Zhouxiang
full_name: Zhao, Zhouxiang
last_name: Zhao
- first_name: Bartholomäus
full_name: Pieber, Bartholomäus
id: 93e5e5b2-0da6-11ed-8a41-af589a024726
last_name: Pieber
orcid: 0000-0001-8689-388X
- first_name: Martina
full_name: Delbianco, Martina
last_name: Delbianco
citation:
ama: Zhao Z, Pieber B, Delbianco M. Modulating the surface and photophysical properties
of carbon dots to access colloidal photocatalysts for cross-couplings. ACS
Catalysis. 2022;12(22):13831-13837. doi:10.1021/acscatal.2c04025
apa: Zhao, Z., Pieber, B., & Delbianco, M. (2022). Modulating the surface and
photophysical properties of carbon dots to access colloidal photocatalysts for
cross-couplings. ACS Catalysis. American Chemical Society. https://doi.org/10.1021/acscatal.2c04025
chicago: Zhao, Zhouxiang, Bartholomäus Pieber, and Martina Delbianco. “Modulating
the Surface and Photophysical Properties of Carbon Dots to Access Colloidal Photocatalysts
for Cross-Couplings.” ACS Catalysis. American Chemical Society, 2022. https://doi.org/10.1021/acscatal.2c04025.
ieee: Z. Zhao, B. Pieber, and M. Delbianco, “Modulating the surface and photophysical
properties of carbon dots to access colloidal photocatalysts for cross-couplings,”
ACS Catalysis, vol. 12, no. 22. American Chemical Society, pp. 13831–13837,
2022.
ista: Zhao Z, Pieber B, Delbianco M. 2022. Modulating the surface and photophysical
properties of carbon dots to access colloidal photocatalysts for cross-couplings.
ACS Catalysis. 12(22), 13831–13837.
mla: Zhao, Zhouxiang, et al. “Modulating the Surface and Photophysical Properties
of Carbon Dots to Access Colloidal Photocatalysts for Cross-Couplings.” ACS
Catalysis, vol. 12, no. 22, American Chemical Society, 2022, pp. 13831–37,
doi:10.1021/acscatal.2c04025.
short: Z. Zhao, B. Pieber, M. Delbianco, ACS Catalysis 12 (2022) 13831–13837.
date_created: 2023-05-08T08:28:54Z
date_published: 2022-10-27T00:00:00Z
date_updated: 2023-05-15T08:30:13Z
day: '27'
doi: 10.1021/acscatal.2c04025
extern: '1'
intvolume: ' 12'
issue: '22'
keyword:
- Catalysis
- General Chemistry
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.1021/acscatal.2c04025
month: '10'
oa: 1
oa_version: Published Version
page: 13831-13837
publication: ACS Catalysis
publication_identifier:
eissn:
- 2155-5435
publication_status: published
publisher: American Chemical Society
quality_controlled: '1'
scopus_import: '1'
status: public
title: Modulating the surface and photophysical properties of carbon dots to access
colloidal photocatalysts for cross-couplings
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 12
year: '2022'
...
---
_id: '12924'
abstract:
- lang: eng
text: We demonstrate that several visible-light-mediated carbon−heteroatom cross-coupling
reactions can be carried out using a photoactive NiII precatalyst that forms in
situ from a nickel salt and a bipyridine ligand decorated with two carbazole groups
(Ni(Czbpy)Cl2). The activation of this precatalyst towards cross-coupling reactions
follows a hitherto undisclosed mechanism that is different from previously reported
light-responsive nickel complexes that undergo metal-to-ligand charge transfer.
Theoretical and spectroscopic investigations revealed that irradiation of Ni(Czbpy)Cl2
with visible light causes an initial intraligand charge transfer event that triggers
productive catalysis. Ligand polymerization affords a porous, recyclable organic
polymer for heterogeneous nickel catalysis of cross-coupling reactions. The heterogeneous
catalyst shows stable performance in a packed-bed flow reactor during a week of
continuous operation.
article_number: e202211433
article_processing_charge: No
article_type: original
author:
- first_name: Cristian
full_name: Cavedon, Cristian
last_name: Cavedon
- first_name: Sebastian
full_name: Gisbertz, Sebastian
last_name: Gisbertz
- first_name: Susanne
full_name: Reischauer, Susanne
last_name: Reischauer
- first_name: Sarah
full_name: Vogl, Sarah
last_name: Vogl
- first_name: Eric
full_name: Sperlich, Eric
last_name: Sperlich
- first_name: John H.
full_name: Burke, John H.
last_name: Burke
- first_name: Rachel F.
full_name: Wallick, Rachel F.
last_name: Wallick
- first_name: Stefanie
full_name: Schrottke, Stefanie
last_name: Schrottke
- first_name: Wei‐Hsin
full_name: Hsu, Wei‐Hsin
last_name: Hsu
- first_name: Lucia
full_name: Anghileri, Lucia
last_name: Anghileri
- first_name: Yannik
full_name: Pfeifer, Yannik
last_name: Pfeifer
- first_name: Noah
full_name: Richter, Noah
last_name: Richter
- first_name: Christian
full_name: Teutloff, Christian
last_name: Teutloff
- first_name: Henrike
full_name: Müller‐Werkmeister, Henrike
last_name: Müller‐Werkmeister
- first_name: Dario
full_name: Cambié, Dario
last_name: Cambié
- first_name: Peter H.
full_name: Seeberger, Peter H.
last_name: Seeberger
- first_name: Josh
full_name: Vura‐Weis, Josh
last_name: Vura‐Weis
- first_name: Renske M.
full_name: van der Veen, Renske M.
last_name: van der Veen
- first_name: Arne
full_name: Thomas, Arne
last_name: Thomas
- first_name: Bartholomäus
full_name: Pieber, Bartholomäus
id: 93e5e5b2-0da6-11ed-8a41-af589a024726
last_name: Pieber
orcid: 0000-0001-8689-388X
citation:
ama: Cavedon C, Gisbertz S, Reischauer S, et al. Intraligand charge transfer enables
visible‐light‐mediated Nickel‐catalyzed cross-coupling reactions. Angewandte
Chemie International Edition. 2022;61(46). doi:10.1002/anie.202211433
apa: Cavedon, C., Gisbertz, S., Reischauer, S., Vogl, S., Sperlich, E., Burke, J.
H., … Pieber, B. (2022). Intraligand charge transfer enables visible‐light‐mediated
Nickel‐catalyzed cross-coupling reactions. Angewandte Chemie International
Edition. Wiley. https://doi.org/10.1002/anie.202211433
chicago: Cavedon, Cristian, Sebastian Gisbertz, Susanne Reischauer, Sarah Vogl,
Eric Sperlich, John H. Burke, Rachel F. Wallick, et al. “Intraligand Charge Transfer
Enables Visible‐light‐mediated Nickel‐catalyzed Cross-Coupling Reactions.” Angewandte
Chemie International Edition. Wiley, 2022. https://doi.org/10.1002/anie.202211433.
ieee: C. Cavedon et al., “Intraligand charge transfer enables visible‐light‐mediated
Nickel‐catalyzed cross-coupling reactions,” Angewandte Chemie International
Edition, vol. 61, no. 46. Wiley, 2022.
ista: Cavedon C, Gisbertz S, Reischauer S, Vogl S, Sperlich E, Burke JH, Wallick
RF, Schrottke S, Hsu W, Anghileri L, Pfeifer Y, Richter N, Teutloff C, Müller‐Werkmeister
H, Cambié D, Seeberger PH, Vura‐Weis J, van der Veen RM, Thomas A, Pieber B. 2022.
Intraligand charge transfer enables visible‐light‐mediated Nickel‐catalyzed cross-coupling
reactions. Angewandte Chemie International Edition. 61(46), e202211433.
mla: Cavedon, Cristian, et al. “Intraligand Charge Transfer Enables Visible‐light‐mediated
Nickel‐catalyzed Cross-Coupling Reactions.” Angewandte Chemie International
Edition, vol. 61, no. 46, e202211433, Wiley, 2022, doi:10.1002/anie.202211433.
short: C. Cavedon, S. Gisbertz, S. Reischauer, S. Vogl, E. Sperlich, J.H. Burke,
R.F. Wallick, S. Schrottke, W. Hsu, L. Anghileri, Y. Pfeifer, N. Richter, C. Teutloff,
H. Müller‐Werkmeister, D. Cambié, P.H. Seeberger, J. Vura‐Weis, R.M. van der Veen,
A. Thomas, B. Pieber, Angewandte Chemie International Edition 61 (2022).
date_created: 2023-05-08T08:30:11Z
date_published: 2022-11-14T00:00:00Z
date_updated: 2023-05-15T08:27:25Z
day: '14'
doi: 10.1002/anie.202211433
extern: '1'
intvolume: ' 61'
issue: '46'
keyword:
- General Chemistry
- Catalysis
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.1002/anie.202211433
month: '11'
oa: 1
oa_version: Published Version
publication: Angewandte Chemie International Edition
publication_identifier:
eissn:
- 1521-3773
issn:
- 1433-7851
publication_status: published
publisher: Wiley
quality_controlled: '1'
scopus_import: '1'
status: public
title: Intraligand charge transfer enables visible‐light‐mediated Nickel‐catalyzed
cross-coupling reactions
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 61
year: '2022'
...
---
_id: '12938'
abstract:
- lang: eng
text: In this work, a feed-forward artificial neural network (FF-ANN) design capable
of locating eigensolutions to Schrödinger's equation via self-supervised learning
is outlined. Based on the input potential determining the nature of the quantum
problem, the presented FF-ANN strategy identifies valid solutions solely by minimizing
Schrödinger's equation encoded in a suitably designed global loss function. In
addition to benchmark calculations of prototype systems with known analytical
solutions, the outlined methodology was also applied to experimentally accessible
quantum systems, such as the vibrational states of molecular hydrogen H2 and its
isotopologues HD and D2 as well as the torsional tunnel splitting in the phenol
molecule. It is shown that in conjunction with the use of SIREN activation functions
a high accuracy in the energy eigenvalues and wavefunctions is achieved without
the requirement to adjust the implementation to the vastly different range of
input potentials, thereby even considering problems under periodic boundary conditions.
article_processing_charge: No
article_type: original
author:
- first_name: Jakob
full_name: Gamper, Jakob
last_name: Gamper
- first_name: Florian
full_name: Kluibenschedl, Florian
id: 7499e70e-eb2c-11ec-b98b-f925648bc9d9
last_name: Kluibenschedl
- first_name: Alexander K. H.
full_name: Weiss, Alexander K. H.
last_name: Weiss
- first_name: Thomas S.
full_name: Hofer, Thomas S.
last_name: Hofer
citation:
ama: Gamper J, Kluibenschedl F, Weiss AKH, Hofer TS. From vibrational spectroscopy
and quantum tunnelling to periodic band structures – a self-supervised, all-purpose
neural network approach to general quantum problems. Physical Chemistry Chemical
Physics. 2022;24(41):25191-25202. doi:10.1039/d2cp03921d
apa: Gamper, J., Kluibenschedl, F., Weiss, A. K. H., & Hofer, T. S. (2022).
From vibrational spectroscopy and quantum tunnelling to periodic band structures
– a self-supervised, all-purpose neural network approach to general quantum problems.
Physical Chemistry Chemical Physics. Royal Society of Chemistry. https://doi.org/10.1039/d2cp03921d
chicago: Gamper, Jakob, Florian Kluibenschedl, Alexander K. H. Weiss, and Thomas
S. Hofer. “From Vibrational Spectroscopy and Quantum Tunnelling to Periodic Band
Structures – a Self-Supervised, All-Purpose Neural Network Approach to General
Quantum Problems.” Physical Chemistry Chemical Physics. Royal Society of
Chemistry, 2022. https://doi.org/10.1039/d2cp03921d.
ieee: J. Gamper, F. Kluibenschedl, A. K. H. Weiss, and T. S. Hofer, “From vibrational
spectroscopy and quantum tunnelling to periodic band structures – a self-supervised,
all-purpose neural network approach to general quantum problems,” Physical
Chemistry Chemical Physics, vol. 24, no. 41. Royal Society of Chemistry, pp.
25191–25202, 2022.
ista: Gamper J, Kluibenschedl F, Weiss AKH, Hofer TS. 2022. From vibrational spectroscopy
and quantum tunnelling to periodic band structures – a self-supervised, all-purpose
neural network approach to general quantum problems. Physical Chemistry Chemical
Physics. 24(41), 25191–25202.
mla: Gamper, Jakob, et al. “From Vibrational Spectroscopy and Quantum Tunnelling
to Periodic Band Structures – a Self-Supervised, All-Purpose Neural Network Approach
to General Quantum Problems.” Physical Chemistry Chemical Physics, vol.
24, no. 41, Royal Society of Chemistry, 2022, pp. 25191–202, doi:10.1039/d2cp03921d.
short: J. Gamper, F. Kluibenschedl, A.K.H. Weiss, T.S. Hofer, Physical Chemistry
Chemical Physics 24 (2022) 25191–25202.
date_created: 2023-05-10T14:48:46Z
date_published: 2022-10-04T00:00:00Z
date_updated: 2023-05-15T07:54:08Z
day: '04'
doi: 10.1039/d2cp03921d
extern: '1'
external_id:
pmid:
- '36254856'
intvolume: ' 24'
issue: '41'
keyword:
- Physical and Theoretical Chemistry
- General Physics and Astronomy
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.1039/D2CP03921D
month: '10'
oa: 1
oa_version: Published Version
page: 25191-25202
pmid: 1
publication: Physical Chemistry Chemical Physics
publication_identifier:
issn:
- 1463-9076
- 1463-9084
publication_status: published
publisher: Royal Society of Chemistry
quality_controlled: '1'
scopus_import: '1'
status: public
title: From vibrational spectroscopy and quantum tunnelling to periodic band structures
– a self-supervised, all-purpose neural network approach to general quantum problems
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 24
year: '2022'
...
---
_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: '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:
record:
- id: '11362'
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:
- access_level: open_access
checksum: 0fc0f852525c10dda9cc9ffea07fb4e4
content_type: application/pdf
creator: mlechner
date_created: 2022-01-26T07:39:59Z
date_updated: 2022-01-26T07:39:59Z
file_id: '10682'
file_name: infinite_time_horizon_safety_o.pdf
file_size: 452492
relation: main_file
success: 1
file_date_updated: 2022-01-26T07:39:59Z
has_accepted_license: '1'
language:
- iso: eng
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
relation: main_file
success: 1
file_date_updated: 2022-01-26T07:38:08Z
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
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file_date_updated: 2022-01-26T07:37:24Z
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language:
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main_file_link:
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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
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short: CC BY-NC-ND (3.0)
type: conference
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...
---
_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'
...