---
OA_place: repository
OA_type: green
_id: '18755'
abstract:
- lang: eng
text: "A universalthresholdizer (UT), constructed from a threshold fully homomorphic
encryption by Boneh et. al , Crypto 2018, is a general framework for universally
thresholdizing many cryptographic schemes. However, their framework is insufficient
to construct strongly secure threshold schemes, such as threshold signatures and
threshold public-key encryption, etc.\r\n\r\nIn this paper, we strengthen the
security definition for a universal thresholdizer and propose a scheme which satisfies
our stronger security notion. Our UT scheme is an improvement of Boneh et. al
’s construction at the level of threshold fully homomorphic encryption using a
key homomorphic pseudorandom function. We apply our strongly secure UT scheme
to construct strongly secure threshold signatures and threshold public-key encryption."
acknowledgement: Ehsan Ebrahimi is supported by the Luxembourg National Research Fund
under the Junior CORE project QSP (C22/IS/17272217/QSP/Ebrahimi).
article_processing_charge: No
author:
- first_name: Ehsan
full_name: Ebrahimi, Ehsan
last_name: Ebrahimi
- first_name: Anshu
full_name: Yadav, Anshu
id: dc8f1524-403e-11ee-bf07-9649ad996e21
last_name: Yadav
citation:
ama: 'Ebrahimi E, Yadav A. Strongly secure universal thresholdizer. In: 30th
International Conference on the Theory and Application of Cryptology and Information
Security. Vol 15486. Springer Nature; 2024:207-239. doi:10.1007/978-981-96-0891-1_7'
apa: 'Ebrahimi, E., & Yadav, A. (2024). Strongly secure universal thresholdizer.
In 30th International Conference on the Theory and Application of Cryptology
and Information Security (Vol. 15486, pp. 207–239). Kolkata, India: Springer
Nature. https://doi.org/10.1007/978-981-96-0891-1_7'
chicago: Ebrahimi, Ehsan, and Anshu Yadav. “Strongly Secure Universal Thresholdizer.”
In 30th International Conference on the Theory and Application of Cryptology
and Information Security, 15486:207–39. Springer Nature, 2024. https://doi.org/10.1007/978-981-96-0891-1_7.
ieee: E. Ebrahimi and A. Yadav, “Strongly secure universal thresholdizer,” in 30th
International Conference on the Theory and Application of Cryptology and Information
Security, Kolkata, India, 2024, vol. 15486, pp. 207–239.
ista: 'Ebrahimi E, Yadav A. 2024. Strongly secure universal thresholdizer. 30th
International Conference on the Theory and Application of Cryptology and Information
Security. ASIACRYPT: Conference on the Theory and Application of Cryptology and
Information Security vol. 15486, 207–239.'
mla: Ebrahimi, Ehsan, and Anshu Yadav. “Strongly Secure Universal Thresholdizer.”
30th International Conference on the Theory and Application of Cryptology and
Information Security, vol. 15486, Springer Nature, 2024, pp. 207–39, doi:10.1007/978-981-96-0891-1_7.
short: E. Ebrahimi, A. Yadav, in:, 30th International Conference on the Theory and
Application of Cryptology and Information Security, Springer Nature, 2024, pp.
207–239.
conference:
end_date: 2024-12-13
location: Kolkata, India
name: 'ASIACRYPT: Conference on the Theory and Application of Cryptology and Information
Security'
start_date: 2024-12-09
date_created: 2025-01-05T23:01:56Z
date_published: 2024-12-12T00:00:00Z
date_updated: 2025-09-09T12:00:12Z
day: '12'
department:
- _id: KrPi
doi: 10.1007/978-981-96-0891-1_7
external_id:
isi:
- '001443889100007'
intvolume: ' 15486'
isi: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://eprint.iacr.org/2024/2078
month: '12'
oa: 1
oa_version: Preprint
page: 207-239
publication: 30th International Conference on the Theory and Application of Cryptology
and Information Security
publication_identifier:
eissn:
- 1611-3349
isbn:
- '9789819608904'
issn:
- 0302-9743
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: Strongly secure universal thresholdizer
type: conference
user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 15486
year: '2024'
...
---
OA_place: repository
OA_type: green
_id: '18756'
abstract:
- lang: eng
text: "The evasive LWE assumption, proposed by Wee [Eurocrypt’22 Wee] for constructing
a lattice-based optimal broadcast encryption, has shown to be a powerful assumption,
adopted by subsequent works to construct advanced primitives ranging from ABE
variants to obfuscation for null circuits. However, a closer look reveals significant
differences among the precise assumption statements involved in different works,
leading to the fundamental question of how these assumptions compare to each other.
In this work, we initiate a more systematic study on evasive LWE assumptions:\r\n(i)
Based on the standard LWE assumption, we construct simple counterexamples against
three private-coin evasive LWE variants, used in [Crypto’22 Tsabary, Asiacrypt’22
VWW, Crypto’23 ARYY] respectively, showing that these assumptions are unlikely
to hold.\r\n\r\n(ii) Based on existing evasive LWE variants and our counterexamples,
we propose and define three classes of plausible evasive LWE assumptions, suitably
capturing all existing variants for which we are not aware of non-obfuscation-based
counterexamples.\r\n\r\n(iii) We show that under our assumption formulations,
the security proofs of [Asiacrypt’22 VWW] and [Crypto’23 ARYY] can be recovered,
and we reason why the security proof of [Crypto’22 Tsabary] is also plausibly
repairable using an appropriate evasive LWE assumption."
acknowledgement: The authors thank the anonymous reviewers for insightful comments
which very much improved this work, in particular, sharing with us the counterexamples
against a prior version of Hiding Evasive LWE, and against public-coin Evasive LWE
when the sampler inputs B. Chris Brzuska and Ivy K. Y. Woo are supported by Research
Council of Finland grant 358950. We thank Russell W. F. Lai and Hoeteck Wee for
helpful discussions.
alternative_title:
- LNCS
article_processing_charge: No
author:
- first_name: Chris
full_name: Brzuska, Chris
last_name: Brzuska
- first_name: Akin
full_name: Ünal, Akin
id: f6b56fb6-dc63-11ee-9dbf-f6780863a85a
last_name: Ünal
orcid: 0000-0002-8929-0221
- first_name: Ivy K.Y.
full_name: Woo, Ivy K.Y.
last_name: Woo
citation:
ama: 'Brzuska C, Ünal A, Woo IKY. Evasive LWE assumptions: Definitions, classes,
and counterexamples. In: 30th International Conference on the Theory and Application
of Cryptology and Information Security. Vol 15487. Springer Nature; 2024:418-449.
doi:10.1007/978-981-96-0894-2_14'
apa: 'Brzuska, C., Ünal, A., & Woo, I. K. Y. (2024). Evasive LWE assumptions:
Definitions, classes, and counterexamples. In 30th International Conference
on the Theory and Application of Cryptology and Information Security (Vol.
15487, pp. 418–449). Kolkata, India: Springer Nature. https://doi.org/10.1007/978-981-96-0894-2_14'
chicago: 'Brzuska, Chris, Akin Ünal, and Ivy K.Y. Woo. “Evasive LWE Assumptions:
Definitions, Classes, and Counterexamples.” In 30th International Conference
on the Theory and Application of Cryptology and Information Security, 15487:418–49.
Springer Nature, 2024. https://doi.org/10.1007/978-981-96-0894-2_14.'
ieee: 'C. Brzuska, A. Ünal, and I. K. Y. Woo, “Evasive LWE assumptions: Definitions,
classes, and counterexamples,” in 30th International Conference on the Theory
and Application of Cryptology and Information Security, Kolkata, India, 2024,
vol. 15487, pp. 418–449.'
ista: 'Brzuska C, Ünal A, Woo IKY. 2024. Evasive LWE assumptions: Definitions, classes,
and counterexamples. 30th International Conference on the Theory and Application
of Cryptology and Information Security. ASIACRYPT: Conference on the Theory and
Application of Cryptology and Information Security, LNCS, vol. 15487, 418–449.'
mla: 'Brzuska, Chris, et al. “Evasive LWE Assumptions: Definitions, Classes, and Counterexamples.”
30th International Conference on the Theory and Application of Cryptology and
Information Security, vol. 15487, Springer Nature, 2024, pp. 418–49, doi:10.1007/978-981-96-0894-2_14.'
short: C. Brzuska, A. Ünal, I.K.Y. Woo, in:, 30th International Conference on the
Theory and Application of Cryptology and Information Security, Springer Nature,
2024, pp. 418–449.
conference:
end_date: 2024-12-13
location: Kolkata, India
name: 'ASIACRYPT: Conference on the Theory and Application of Cryptology and Information
Security'
start_date: 2024-12-09
date_created: 2025-01-05T23:01:56Z
date_published: 2024-12-13T00:00:00Z
date_updated: 2025-09-09T12:00:51Z
day: '13'
department:
- _id: KrPi
doi: 10.1007/978-981-96-0894-2_14
external_id:
isi:
- '001443890800014'
intvolume: ' 15487'
isi: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://eprint.iacr.org/2024/2000
month: '12'
oa: 1
oa_version: Preprint
page: 418-449
publication: 30th International Conference on the Theory and Application of Cryptology
and Information Security
publication_identifier:
eissn:
- 1611-3349
isbn:
- '9789819608935'
issn:
- 0302-9743
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'Evasive LWE assumptions: Definitions, classes, and counterexamples'
type: conference
user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 15487
year: '2024'
...
---
DOAJ_listed: '1'
OA_place: publisher
OA_type: gold
_id: '18757'
abstract:
- lang: eng
text: 'Segmentation is a critical data processing step in many applications of cryo-electron
tomography. Downstream analyses, such as subtomogram averaging, are often based
on segmentation results, and are thus critically dependent on the availability
of open-source software for accurate as well as high-throughput tomogram segmentation.
There is a need for more user-friendly, flexible, and comprehensive segmentation
software that offers an insightful overview of all steps involved in preparing
automated segmentations. Here, we present Ais: a dedicated tomogram segmentation
package that is geared towards both high performance and accessibility, available
on GitHub. In this report, we demonstrate two common processing steps that can
be greatly accelerated with Ais: particle picking for subtomogram averaging, and
generating many-feature segmentations of cellular architecture based on in situ
tomography data. Featuring comprehensive annotation, segmentation, and rendering
functionality, as well as an open repository for trained models at aiscryoet.org,
we hope that Ais will help accelerate research and dissemination of data involving
cryoET.'
acknowledgement: 'We thank A Koster and M Barcena for helpful discussions and kindly
sharing the coronaviral replication organelle datasets. We are also grateful to
van den Hoek et al., 2022 and Wu et al., 2023, for uploading the data that we used
for Figure 5 onto EMPIAR and EMDB, as well as to the authors of various other datasets
uploaded to these databases that are not discussed in this manuscript but that were
useful for testing the software. We also thank the reviewers, whose comments were
very helpful in improving the manuscript and the software. Finally, we are grateful
the early Ais users who provided us with feedback on the software and reported issues.
This research was supported by the following grants to THS: European Research Council
H202 Grant 759517; European Union’s Horizon Europe Program IMAGINE grant 101094250,
and the Netherlands Organization for Scientific Research Grant VI.Vidi.193.014.'
article_number: '98552'
article_processing_charge: Yes
article_type: original
author:
- first_name: Mart G.F.
full_name: Last, Mart G.F.
last_name: Last
- first_name: Leoni
full_name: Abendstein, Leoni
id: 14f1f051-cd9d-11ef-9c94-8b942a882560
last_name: Abendstein
orcid: 0000-0001-7634-5353
- first_name: Lenard M.
full_name: Voortman, Lenard M.
last_name: Voortman
- first_name: Thomas H.
full_name: Sharp, Thomas H.
last_name: Sharp
citation:
ama: Last MGF, Abendstein L, Voortman LM, Sharp TH. Streamlining segmentation of
cryo-electron tomography datasets with Ais. eLife. 2024;13. doi:10.7554/eLife.98552
apa: Last, M. G. F., Abendstein, L., Voortman, L. M., & Sharp, T. H. (2024).
Streamlining segmentation of cryo-electron tomography datasets with Ais. ELife.
eLife Sciences Publications. https://doi.org/10.7554/eLife.98552
chicago: Last, Mart G.F., Leoni Abendstein, Lenard M. Voortman, and Thomas H. Sharp.
“Streamlining Segmentation of Cryo-Electron Tomography Datasets with Ais.” ELife.
eLife Sciences Publications, 2024. https://doi.org/10.7554/eLife.98552.
ieee: M. G. F. Last, L. Abendstein, L. M. Voortman, and T. H. Sharp, “Streamlining
segmentation of cryo-electron tomography datasets with Ais,” eLife, vol.
13. eLife Sciences Publications, 2024.
ista: Last MGF, Abendstein L, Voortman LM, Sharp TH. 2024. Streamlining segmentation
of cryo-electron tomography datasets with Ais. eLife. 13, 98552.
mla: Last, Mart G. F., et al. “Streamlining Segmentation of Cryo-Electron Tomography
Datasets with Ais.” ELife, vol. 13, 98552, eLife Sciences Publications,
2024, doi:10.7554/eLife.98552.
short: M.G.F. Last, L. Abendstein, L.M. Voortman, T.H. Sharp, ELife 13 (2024).
date_created: 2025-01-05T23:01:57Z
date_published: 2024-12-20T00:00:00Z
date_updated: 2025-01-08T08:52:51Z
day: '20'
ddc:
- '570'
department:
- _id: FlPr
doi: 10.7554/eLife.98552
external_id:
pmid:
- '39704648'
file:
- access_level: open_access
checksum: a4f0f906e4d5c1078208b317e78699d1
content_type: application/pdf
creator: dernst
date_created: 2025-01-08T08:51:45Z
date_updated: 2025-01-08T08:51:45Z
file_id: '18774'
file_name: 2024_eLife_Last.pdf
file_size: 7445664
relation: main_file
success: 1
file_date_updated: 2025-01-08T08:51:45Z
has_accepted_license: '1'
intvolume: ' 13'
language:
- iso: eng
license: https://creativecommons.org/licenses/by/4.0/
month: '12'
oa: 1
oa_version: Published Version
pmid: 1
publication: eLife
publication_identifier:
eissn:
- 2050-084X
publication_status: published
publisher: eLife Sciences Publications
quality_controlled: '1'
scopus_import: '1'
status: public
title: Streamlining segmentation of cryo-electron tomography datasets with Ais
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: 13
year: '2024'
...
---
OA_place: publisher
OA_type: gold
_id: '18758'
abstract:
- lang: eng
text: 'MaxCut is a classical NP-complete problem and a crucial building block in
many combinatorial algorithms. The famous Edwards-Erdős bound states that any
connected graph on n vertices with m edges contains a cut of size at least m/2+(n-1)/4.
Crowston, Jones and Mnich [Algorithmica, 2015] showed that the MaxCut problem
on simple connected graphs admits an FPT algorithm, where the parameter k is the
difference between the desired cut size c and the lower bound given by the Edwards-Erdős
bound. This was later improved by Etscheid and Mnich [Algorithmica, 2017] to run
in parameterized linear time, i.e., f(k)⋅ O(m). We improve upon this result in
two ways: Firstly, we extend the algorithm to work also for multigraphs (alternatively,
graphs with positive integer weights). Secondly, we change the parameter; instead
of the difference to the Edwards-Erdős bound, we use the difference to the Poljak-Turzík
bound. The Poljak-Turzík bound states that any weighted graph G has a cut of size
at least (w(G))/2+(w_MSF(G))/4, where w(G) denotes the total weight of G, and
w_MSF(G) denotes the weight of its minimum spanning forest. In connected simple
graphs the two bounds are equivalent, but for multigraphs the Poljak-Turzík bound
can be larger and thus yield a smaller parameter k. Our algorithm also runs in
parameterized linear time, i.e., f(k)⋅ O(m+n).'
acknowledgement: "Kalina Petrova: Swiss National Science Foundation, grant no. CRSII5
173721. This project\r\nhas received funding from the European Union’s Horizon 2020
research and innovation programme under the Marie Skłodowska-Curie grant agreement
No 101034413.\r\nSimon Weber: Swiss National Science Foundation under project no.
204320"
alternative_title:
- LIPIcs
article_number: '2'
article_processing_charge: Yes
arxiv: 1
author:
- first_name: Jonas
full_name: Lill, Jonas
last_name: Lill
- first_name: Kalina H
full_name: Petrova, Kalina H
id: 554ff4e4-f325-11ee-b0c4-a10dbd523381
last_name: Petrova
- first_name: Simon
full_name: Weber, Simon
last_name: Weber
citation:
ama: 'Lill J, Petrova KH, Weber S. Linear-time MaxCut in multigraphs parameterized
above the Poljak-Turzík bound. In: 19th International Symposium on Parameterized
and Exact Computation. Vol 321. Schloss Dagstuhl - Leibniz-Zentrum für Informatik;
2024. doi:10.4230/LIPIcs.IPEC.2024.2'
apa: 'Lill, J., Petrova, K. H., & Weber, S. (2024). Linear-time MaxCut in multigraphs
parameterized above the Poljak-Turzík bound. In 19th International Symposium
on Parameterized and Exact Computation (Vol. 321). Egham, United Kingdom:
Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.IPEC.2024.2'
chicago: Lill, Jonas, Kalina H Petrova, and Simon Weber. “Linear-Time MaxCut in
Multigraphs Parameterized above the Poljak-Turzík Bound.” In 19th International
Symposium on Parameterized and Exact Computation, Vol. 321. Schloss Dagstuhl
- Leibniz-Zentrum für Informatik, 2024. https://doi.org/10.4230/LIPIcs.IPEC.2024.2.
ieee: J. Lill, K. H. Petrova, and S. Weber, “Linear-time MaxCut in multigraphs parameterized
above the Poljak-Turzík bound,” in 19th International Symposium on Parameterized
and Exact Computation, Egham, United Kingdom, 2024, vol. 321.
ista: 'Lill J, Petrova KH, Weber S. 2024. Linear-time MaxCut in multigraphs parameterized
above the Poljak-Turzík bound. 19th International Symposium on Parameterized and
Exact Computation. IPEC: Symposium on Parameterized and Exact Computation, LIPIcs,
vol. 321, 2.'
mla: Lill, Jonas, et al. “Linear-Time MaxCut in Multigraphs Parameterized above
the Poljak-Turzík Bound.” 19th International Symposium on Parameterized and
Exact Computation, vol. 321, 2, Schloss Dagstuhl - Leibniz-Zentrum für Informatik,
2024, doi:10.4230/LIPIcs.IPEC.2024.2.
short: J. Lill, K.H. Petrova, S. Weber, in:, 19th International Symposium on Parameterized
and Exact Computation, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2024.
conference:
end_date: 2024-09-06
location: Egham, United Kingdom
name: 'IPEC: Symposium on Parameterized and Exact Computation'
start_date: 2024-09-04
corr_author: '1'
date_created: 2025-01-05T23:01:57Z
date_published: 2024-12-05T00:00:00Z
date_updated: 2026-01-05T13:46:07Z
day: '05'
ddc:
- '500'
department:
- _id: MaKw
doi: 10.4230/LIPIcs.IPEC.2024.2
ec_funded: 1
external_id:
arxiv:
- '2407.01071'
isi:
- '001534851900002'
file:
- access_level: open_access
checksum: a64b9a0e41f7b867d25cb155825ccd53
content_type: application/pdf
creator: dernst
date_created: 2025-01-08T09:14:59Z
date_updated: 2025-01-08T09:14:59Z
file_id: '18775'
file_name: 2024_LIPIcs_Lill.pdf
file_size: 927326
relation: main_file
success: 1
file_date_updated: 2025-01-08T09:14:59Z
has_accepted_license: '1'
intvolume: ' 321'
isi: 1
language:
- iso: eng
month: '12'
oa: 1
oa_version: Published Version
project:
- _id: fc2ed2f7-9c52-11eb-aca3-c01059dda49c
call_identifier: H2020
grant_number: '101034413'
name: 'IST-BRIDGE: International postdoctoral program'
publication: 19th International Symposium on Parameterized and Exact Computation
publication_identifier:
isbn:
- '9783959773539'
issn:
- 1868-8969
publication_status: published
publisher: Schloss Dagstuhl - Leibniz-Zentrum für Informatik
quality_controlled: '1'
related_material:
record:
- id: '19603'
relation: later_version
status: public
scopus_import: '1'
status: public
title: Linear-time MaxCut in multigraphs parameterized above the Poljak-Turzík bound
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: 321
year: '2024'
...
---
DOAJ_listed: '1'
OA_place: publisher
OA_type: gold
_id: '18760'
abstract:
- lang: eng
text: With the remarkable sensitivity and resolution of JWST in the infrared, measuring
rest-optical kinematics of galaxies at z > 5 has become possible for the first
time. This study pilots a new method for measuring galaxy dynamics for highly
multiplexed, unbiased samples by combining FRESCO NIRCam grism spectroscopy and
JADES medium-band imaging. Here we present one of the first JWST kinematic measurements
for a galaxy at z > 5. We find a significant velocity gradient, which, if interpreted
as rotation, yields Vrot = 305 ± 70 km s−1, and we hence refer to this galaxy
as Twister-z5. With a rest-frame optical effective radius of re = 2.25 kpc, the
high rotation velocity in this galaxy is not due to a compact size, as may be
expected in the early Universe, but rather to a high total mass, (math formula).
This is a factor of roughly 10× higher than the stellar mass within re. We also
observe that the radial Hα equivalent width profile and the specific star formation
rate map from resolved stellar population modeling are centrally depressed by
a factor of ∼1.5 from the center to re. Combined with the morphology of the line-emitting
gas in comparison to the continuum, this centrally suppressed star formation is
consistent with a star-forming disk surrounding a bulge growing inside out. While
large, rapidly rotating disks are common to z ∼ 2, the existence of one after
only 1 Gyr of cosmic time, shown for the first time in ionized gas, adds to the
growing evidence that some galaxies matured earlier than expected in the history
of the Universe.
acknowledgement: We thank the reviewer and editorial staff for their excellent feedback
and effort—the manuscript is much stronger as a result. Support for this work was
provided by NASA through grant JWST-GO-01895 awarded by the Space Telescope Science
Institute, which is operated by the Association of Universities for Research in
Astronomy, Inc., under NASA contract NAS 5-26555. H.Ü. gratefully acknowledges support
by the Isaac Newton Trust and by the Kavli Foundation through a Newton-Kavli Junior
Fellowship. This work has received funding from the Swiss State Secretariat for
Education, Research and Innovation (SERI) under contract No. MB22.00072, as well
as from the Swiss National Science Foundation (SNSF) through project grant 200020_207349.
The Cosmic Dawn Center (DAWN) is funded by the Danish National Research Foundation
under grant No. 140. R.S. acknowledges an STFC Ernest Rutherford Fellowship (ST/S004831/1).
R.P.N. acknowledges support for this work provided by NASA through the NASA Hubble
Fellowship grant HST-HF2-51515.001-A awarded by the Space Telescope Science Institute,
which is operated by the Association of Universities for Research in Astronomy,
Inc., under NASA contract NAS5-26555. M.V.M. acknowledges support from the National
Science Foundation via AAG grant 2205519 and the Wisconsin Alumni Research Foundation
via grant MSN251397. R.M. also acknowledges funding from a research professorship
from the Royal Society. A.J.B., A.J.C., and G.C.J. acknowledge funding from the
"FirstGalaxies" Advanced Grant from the European Research Council (ERC) under the
European Union's Horizon 2020 research and innovation program (grant agreement No.
789056). I.L. acknowledges support by the Australian Research Council through Future
Fellowship FT220100798. D.J.E. is supported as a Simons Investigator and by a JWST/NIRCam
contract to the University of Arizona, NAS5-02015. R.M., J.W., L.S., and W.B. acknowledge
support by the Science and Technology Facilities Council (STFC), the ERC through
advanced grant 695671 "QUENCH," and the UKRI Frontier Research grant RISEandFALL.
B.E.R. acknowledges support from the NIRCam Science Team contract to the University
of Arizona, NAS5-02015. The research of C.C.W. is supported by NOIRLab, which is
managed by the Association of Universities for Research in Astronomy (AURA) under
a cooperative agreement with the National Science Foundation. The HST and JWST image
mosaics of the FRESCO fields are released at MAST as a High Level Science Product
(P. Oesch & D. Magee 2023).
article_number: L27
article_processing_charge: Yes
article_type: letter_note
arxiv: 1
author:
- first_name: Erica
full_name: Nelson, Erica
last_name: Nelson
- first_name: Gabriel
full_name: Brammer, Gabriel
last_name: Brammer
- first_name: Clara
full_name: Giménez-Arteaga, Clara
last_name: Giménez-Arteaga
- first_name: Pascal A.
full_name: Oesch, Pascal A.
last_name: Oesch
- first_name: Rohan P.
full_name: Naidu, Rohan P.
last_name: Naidu
- first_name: Hannah
full_name: Übler, Hannah
last_name: Übler
- first_name: Jasleen
full_name: Matharu, Jasleen
last_name: Matharu
- first_name: Alice E.
full_name: Shapley, Alice E.
last_name: Shapley
- first_name: Katherine E.
full_name: Whitaker, Katherine E.
last_name: Whitaker
- first_name: Emily
full_name: Wisnioski, Emily
last_name: Wisnioski
- first_name: Natascha M.
full_name: Förster Schreiber, Natascha M.
last_name: Förster Schreiber
- first_name: Renske
full_name: Smit, Renske
last_name: Smit
- first_name: Pieter
full_name: Van Dokkum, Pieter
last_name: Van Dokkum
- first_name: John
full_name: Chisholm, John
last_name: Chisholm
- first_name: Ryan
full_name: Endsley, Ryan
last_name: Endsley
- first_name: Abigail I.
full_name: Hartley, Abigail I.
last_name: Hartley
- first_name: Justus
full_name: Gibson, Justus
last_name: Gibson
- first_name: Emma
full_name: Giovinazzo, Emma
last_name: Giovinazzo
- first_name: Garth
full_name: Illingworth, Garth
last_name: Illingworth
- first_name: Ivo
full_name: Labbe, Ivo
last_name: Labbe
- first_name: Michael V.
full_name: Maseda, Michael V.
last_name: Maseda
- first_name: Jorryt J
full_name: Matthee, Jorryt J
id: 7439a258-f3c0-11ec-9501-9df22fe06720
last_name: Matthee
orcid: 0000-0003-2871-127X
- first_name: Alba
full_name: Covelo Paz, Alba
last_name: Covelo Paz
- first_name: Sedona H.
full_name: Price, Sedona H.
last_name: Price
- first_name: Naveen A.
full_name: Reddy, Naveen A.
last_name: Reddy
- first_name: Irene
full_name: Shivaei, Irene
last_name: Shivaei
- first_name: Andrea
full_name: Weibel, Andrea
last_name: Weibel
- first_name: Stijn
full_name: Wuyts, Stijn
last_name: Wuyts
- first_name: Mengyuan
full_name: Xiao, Mengyuan
last_name: Xiao
- first_name: Stacey
full_name: Alberts, Stacey
last_name: Alberts
- first_name: William M.
full_name: Baker, William M.
last_name: Baker
- first_name: Andrew J.
full_name: Bunker, Andrew J.
last_name: Bunker
- first_name: Alex J.
full_name: Cameron, Alex J.
last_name: Cameron
- first_name: Stephane
full_name: Charlot, Stephane
last_name: Charlot
- first_name: Daniel J.
full_name: Eisenstein, Daniel J.
last_name: Eisenstein
- first_name: Anna
full_name: De Graaff, Anna
last_name: De Graaff
- first_name: Zhiyuan
full_name: Ji, Zhiyuan
last_name: Ji
- first_name: Benjamin D.
full_name: Johnson, Benjamin D.
last_name: Johnson
- first_name: Gareth C.
full_name: Jones, Gareth C.
last_name: Jones
- first_name: Roberto
full_name: Maiolino, Roberto
last_name: Maiolino
- first_name: Brant
full_name: Robertson, Brant
last_name: Robertson
- first_name: Lester
full_name: Sandles, Lester
last_name: Sandles
- first_name: Katherine A.
full_name: Suess, Katherine A.
last_name: Suess
- first_name: Sandro
full_name: Tacchella, Sandro
last_name: Tacchella
- first_name: Christina C.
full_name: Williams, Christina C.
last_name: Williams
- first_name: Joris
full_name: Witstok, Joris
last_name: Witstok
citation:
ama: 'Nelson E, Brammer G, Giménez-Arteaga C, et al. Ionized gas kinematics with
FRESCO: An extended, massive, rapidly rotating galaxy at z = 5.4. Astrophysical
Journal Letters. 2024;976(2). doi:10.3847/2041-8213/ad7b17'
apa: 'Nelson, E., Brammer, G., Giménez-Arteaga, C., Oesch, P. A., Naidu, R. P.,
Übler, H., … Witstok, J. (2024). Ionized gas kinematics with FRESCO: An extended,
massive, rapidly rotating galaxy at z = 5.4. Astrophysical Journal Letters.
IOP Publishing. https://doi.org/10.3847/2041-8213/ad7b17'
chicago: 'Nelson, Erica, Gabriel Brammer, Clara Giménez-Arteaga, Pascal A. Oesch,
Rohan P. Naidu, Hannah Übler, Jasleen Matharu, et al. “Ionized Gas Kinematics
with FRESCO: An Extended, Massive, Rapidly Rotating Galaxy at z = 5.4.” Astrophysical
Journal Letters. IOP Publishing, 2024. https://doi.org/10.3847/2041-8213/ad7b17.'
ieee: 'E. Nelson et al., “Ionized gas kinematics with FRESCO: An extended,
massive, rapidly rotating galaxy at z = 5.4,” Astrophysical Journal Letters,
vol. 976, no. 2. IOP Publishing, 2024.'
ista: 'Nelson E, Brammer G, Giménez-Arteaga C, Oesch PA, Naidu RP, Übler H, Matharu
J, Shapley AE, Whitaker KE, Wisnioski E, Förster Schreiber NM, Smit R, Van Dokkum
P, Chisholm J, Endsley R, Hartley AI, Gibson J, Giovinazzo E, Illingworth G, Labbe
I, Maseda MV, Matthee JJ, Covelo Paz A, Price SH, Reddy NA, Shivaei I, Weibel
A, Wuyts S, Xiao M, Alberts S, Baker WM, Bunker AJ, Cameron AJ, Charlot S, Eisenstein
DJ, De Graaff A, Ji Z, Johnson BD, Jones GC, Maiolino R, Robertson B, Sandles
L, Suess KA, Tacchella S, Williams CC, Witstok J. 2024. Ionized gas kinematics
with FRESCO: An extended, massive, rapidly rotating galaxy at z = 5.4. Astrophysical
Journal Letters. 976(2), L27.'
mla: 'Nelson, Erica, et al. “Ionized Gas Kinematics with FRESCO: An Extended, Massive,
Rapidly Rotating Galaxy at z = 5.4.” Astrophysical Journal Letters, vol.
976, no. 2, L27, IOP Publishing, 2024, doi:10.3847/2041-8213/ad7b17.'
short: E. Nelson, G. Brammer, C. Giménez-Arteaga, P.A. Oesch, R.P. Naidu, H. Übler,
J. Matharu, A.E. Shapley, K.E. Whitaker, E. Wisnioski, N.M. Förster Schreiber,
R. Smit, P. Van Dokkum, J. Chisholm, R. Endsley, A.I. Hartley, J. Gibson, E. Giovinazzo,
G. Illingworth, I. Labbe, M.V. Maseda, J.J. Matthee, A. Covelo Paz, S.H. Price,
N.A. Reddy, I. Shivaei, A. Weibel, S. Wuyts, M. Xiao, S. Alberts, W.M. Baker,
A.J. Bunker, A.J. Cameron, S. Charlot, D.J. Eisenstein, A. De Graaff, Z. Ji, B.D.
Johnson, G.C. Jones, R. Maiolino, B. Robertson, L. Sandles, K.A. Suess, S. Tacchella,
C.C. Williams, J. Witstok, Astrophysical Journal Letters 976 (2024).
date_created: 2025-01-05T23:01:58Z
date_published: 2024-12-01T00:00:00Z
date_updated: 2025-09-09T11:58:02Z
day: '01'
ddc:
- '520'
department:
- _id: JoMa
doi: 10.3847/2041-8213/ad7b17
external_id:
arxiv:
- '2310.06887'
isi:
- '001364636000001'
file:
- access_level: open_access
checksum: 5c7320196586b4340e55f215d8737185
content_type: application/pdf
creator: dernst
date_created: 2025-01-08T08:18:39Z
date_updated: 2025-01-08T08:18:39Z
file_id: '18771'
file_name: 2024_AstrophysicalJour_Nelson.pdf
file_size: 1822989
relation: main_file
success: 1
file_date_updated: 2025-01-08T08:18:39Z
has_accepted_license: '1'
intvolume: ' 976'
isi: 1
issue: '2'
language:
- iso: eng
month: '12'
oa: 1
oa_version: Published Version
publication: Astrophysical Journal Letters
publication_identifier:
eissn:
- 2041-8213
issn:
- 2041-8205
publication_status: published
publisher: IOP Publishing
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'Ionized gas kinematics with FRESCO: An extended, massive, rapidly rotating
galaxy at z = 5.4'
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: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 976
year: '2024'
...
---
DOAJ_listed: '1'
OA_place: publisher
OA_type: gold
_id: '18761'
abstract:
- lang: eng
text: Termites, together with cockroaches, belong to the Blattodea. They possess
an XX/XY sex determination system which has evolved from an XX/X0 system present
in other Blattodean species, such as cockroaches and wood roaches. Little is currently
known about the sex chromosomes of termites, their gene content, or their evolution.
We here investigate the X chromosome of multiple termite species and compare them
with the X chromosome of cockroaches using genomic and transcriptomic data. We
find that the X chromosome of the termite Macrotermes natalensis is large and
differentiated showing hall marks of sex chromosome evolution such as dosage compensation,
while this does not seem to be the case in the other two termite species investigated
here where sex chromosomes may be evolutionary younger. Furthermore, the X chromosome
in M. natalensis is different from the X chromosome found in the cockroach Blattella
germanica indicating that sex chromosome turn-over events may have happened during
termite evolution.
acknowledged_ssus:
- _id: ScienComp
acknowledgement: "urthermore, we thank all lab members and collaborators for feedback
on the project. Specifically, Dino McMahon provided R. flavipes males and females,
Judith Korb provided C. secundus males and females, gave feedback on the project
and discussed questions on termite reproduction, Mireille Vasseur-Cognet provided
M. natalensis males and females, Ariana Macon performed the lab work for sequencing
and the Vicoso group gave critical feedback on the project. We furthermore thank
the HPC group at IST Austria and Christian Meesters at JGU Mainz for their technical
support.\r\nThis work was supported by a Österreichischer Wissenschaftsfonds (FWF)
grant of the Meitner Programme to A.K.H. (project number M 2484), funding by the
Deutsche Forschungsgemeinschaft (DFG) of the Research Training Group GenEvo (project
number 407023052) to A.K.H., R.F., and A.D., and funding of the DFG within the Schwerpunktprogramm
Gevol to A.K.H. and R.M. (project number 503256468)."
article_number: evae265
article_processing_charge: Yes
article_type: original
author:
- first_name: Roxanne
full_name: Fraser, Roxanne
last_name: Fraser
- first_name: Ruth
full_name: Moraa, Ruth
last_name: Moraa
- first_name: Annika
full_name: Djolai, Annika
last_name: Djolai
- first_name: Nils
full_name: Meisenheimer, Nils
last_name: Meisenheimer
- first_name: Sophie
full_name: Laube, Sophie
last_name: Laube
- first_name: Beatriz
full_name: Vicoso, Beatriz
id: 49E1C5C6-F248-11E8-B48F-1D18A9856A87
last_name: Vicoso
orcid: 0000-0002-4579-8306
- first_name: Ann K
full_name: Huylmans, Ann K
id: 4C0A3874-F248-11E8-B48F-1D18A9856A87
last_name: Huylmans
orcid: 0000-0001-8871-4961
citation:
ama: Fraser R, Moraa R, Djolai A, et al. Evidence for a novel X chromosome in termites.
Genome Biology and Evolution. 2024;16(12). doi:10.1093/gbe/evae265
apa: Fraser, R., Moraa, R., Djolai, A., Meisenheimer, N., Laube, S., Vicoso, B.,
& Huylmans, A. K. (2024). Evidence for a novel X chromosome in termites. Genome
Biology and Evolution. Oxford University Press. https://doi.org/10.1093/gbe/evae265
chicago: Fraser, Roxanne, Ruth Moraa, Annika Djolai, Nils Meisenheimer, Sophie Laube,
Beatriz Vicoso, and Ann K Huylmans. “Evidence for a Novel X Chromosome in Termites.”
Genome Biology and Evolution. Oxford University Press, 2024. https://doi.org/10.1093/gbe/evae265.
ieee: R. Fraser et al., “Evidence for a novel X chromosome in termites,”
Genome Biology and Evolution, vol. 16, no. 12. Oxford University Press,
2024.
ista: Fraser R, Moraa R, Djolai A, Meisenheimer N, Laube S, Vicoso B, Huylmans AK.
2024. Evidence for a novel X chromosome in termites. Genome Biology and Evolution.
16(12), evae265.
mla: Fraser, Roxanne, et al. “Evidence for a Novel X Chromosome in Termites.” Genome
Biology and Evolution, vol. 16, no. 12, evae265, Oxford University Press,
2024, doi:10.1093/gbe/evae265.
short: R. Fraser, R. Moraa, A. Djolai, N. Meisenheimer, S. Laube, B. Vicoso, A.K.
Huylmans, Genome Biology and Evolution 16 (2024).
corr_author: '1'
date_created: 2025-01-05T23:01:58Z
date_published: 2024-12-01T00:00:00Z
date_updated: 2025-09-09T11:58:41Z
day: '01'
ddc:
- '570'
department:
- _id: BeVi
doi: 10.1093/gbe/evae265
external_id:
isi:
- '001380841100001'
pmid:
- '39658246'
file:
- access_level: open_access
checksum: 9cf8fd14580dd694dd810ccca808ad0e
content_type: application/pdf
creator: dernst
date_created: 2025-01-08T08:28:07Z
date_updated: 2025-01-08T08:28:07Z
file_id: '18772'
file_name: 2024_GBE_Fraser.pdf
file_size: 795106
relation: main_file
success: 1
file_date_updated: 2025-01-08T08:28:07Z
has_accepted_license: '1'
intvolume: ' 16'
isi: 1
issue: '12'
language:
- iso: eng
license: https://creativecommons.org/licenses/by-nc/4.0/
month: '12'
oa: 1
oa_version: Published Version
pmid: 1
project:
- _id: 26641CAC-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: M02484
name: Sex Determination in Termites
publication: Genome Biology and Evolution
publication_identifier:
eissn:
- 1759-6653
publication_status: published
publisher: Oxford University Press
quality_controlled: '1'
scopus_import: '1'
status: public
title: Evidence for a novel X chromosome in termites
tmp:
image: /images/cc_by_nc.png
legal_code_url: https://creativecommons.org/licenses/by-nc/4.0/legalcode
name: Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)
short: CC BY-NC (4.0)
type: journal_article
user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 16
year: '2024'
...
---
DOAJ_listed: '1'
OA_place: publisher
OA_type: gold
_id: '18762'
abstract:
- lang: eng
text: Consider the random variable $\mathrm{Tr}( f_1(W)A_1\dots f_k(W)A_k)$ where
$W$ is an $N\times N$ Hermitian Wigner matrix, $k\in\mathbb{N}$, and choose (possibly
$N$-dependent) regular functions $f_1,\dots, f_k$ as well as bounded deterministic
matrices $A_1,\dots,A_k$. We give a functional central limit theorem showing that
the fluctuations around the expectation are Gaussian. Moreover, we determine the
limiting covariance structure and give explicit error bounds in terms of the scaling
of $f_1,\dots,f_k$ and the number of traceless matrices among $A_1,\dots,A_k$,
thus extending the results of [Cipolloni, Erdős, Schröder 2023] to products of
arbitrary length $k\geq2$. As an application, we consider the fluctuation of $\mathrm{Tr}(\mathrm{e}^{\mathrm{i}
tW}A_1\mathrm{e}^{-\mathrm{i} tW}A_2)$ around its thermal value $\mathrm{Tr}(A_1)\mathrm{Tr}(A_2)$
when $t$ is large and give an explicit formula for the variance.
acknowledgement: "I am very grateful to László Erdős for suggesting the topic and
many valuable discussions during my work on the project. I would also like to thank
the two anonymous referees for their careful reading of the manuscript and detailed
feedback.\r\nPartially supported by ERC Advanced Grants “RMTBeyond” No. 101020331
and “LDRaM” No. 884584."
article_number: '191'
article_processing_charge: Yes
article_type: original
arxiv: 1
author:
- first_name: Jana
full_name: Reker, Jana
id: e796e4f9-dc8d-11ea-abe3-97e26a0323e9
last_name: Reker
citation:
ama: Reker J. Multi-point functional central limit theorem for Wigner matrices.
Electronic Journal of Probability. 2024;29. doi:10.1214/24-EJP1247
apa: Reker, J. (2024). Multi-point functional central limit theorem for Wigner matrices.
Electronic Journal of Probability. Institute of Mathematical Statistics.
https://doi.org/10.1214/24-EJP1247
chicago: Reker, Jana. “Multi-Point Functional Central Limit Theorem for Wigner Matrices.”
Electronic Journal of Probability. Institute of Mathematical Statistics,
2024. https://doi.org/10.1214/24-EJP1247.
ieee: J. Reker, “Multi-point functional central limit theorem for Wigner matrices,”
Electronic Journal of Probability, vol. 29. Institute of Mathematical Statistics,
2024.
ista: Reker J. 2024. Multi-point functional central limit theorem for Wigner matrices.
Electronic Journal of Probability. 29, 191.
mla: Reker, Jana. “Multi-Point Functional Central Limit Theorem for Wigner Matrices.”
Electronic Journal of Probability, vol. 29, 191, Institute of Mathematical
Statistics, 2024, doi:10.1214/24-EJP1247.
short: J. Reker, Electronic Journal of Probability 29 (2024).
corr_author: '1'
date_created: 2025-01-05T23:01:58Z
date_published: 2024-12-20T00:00:00Z
date_updated: 2025-09-09T11:59:15Z
day: '20'
ddc:
- '510'
department:
- _id: LaEr
doi: 10.1214/24-EJP1247
ec_funded: 1
external_id:
arxiv:
- '2307.11028'
isi:
- '001381599200001'
file:
- access_level: open_access
checksum: 67178feaa8630a332599d3037a3fe70e
content_type: application/pdf
creator: dernst
date_created: 2025-01-08T08:44:03Z
date_updated: 2025-01-08T08:44:03Z
file_id: '18773'
file_name: 2024_ElectrJournProbability_Reker.pdf
file_size: 812428
relation: main_file
success: 1
file_date_updated: 2025-01-08T08:44:03Z
has_accepted_license: '1'
intvolume: ' 29'
isi: 1
language:
- iso: eng
month: '12'
oa: 1
oa_version: Published Version
project:
- _id: 62796744-2b32-11ec-9570-940b20777f1d
call_identifier: H2020
grant_number: '101020331'
name: Random matrices beyond Wigner-Dyson-Mehta
publication: Electronic Journal of Probability
publication_identifier:
eissn:
- 1083-6489
publication_status: published
publisher: Institute of Mathematical Statistics
quality_controlled: '1'
related_material:
record:
- id: '17173'
relation: earlier_version
status: public
scopus_import: '1'
status: public
title: Multi-point functional central limit theorem for Wigner matrices
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: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 29
year: '2024'
...
---
OA_place: publisher
_id: '18766'
abstract:
- lang: eng
text: Poxviruses are large pleomorphic double-stranded DNA viruses that include
well known members such as variola virus, the causative agent of smallpox, Mpox
virus, as well as Vaccinia virus (VACV), which serves as a vaccination strain
for formerly mentioned viruses. VACV is a valuable model for studying large pleomorphic
DNA viruses in general and poxviruses specifically, as many features, such as
core morphology and structural proteins, are well conserved within this family.
Despite decades of research, our understanding of the structural components and
proteins that comprise the poxvirus core in mature virions remains limited. Although
major core proteins were identified via indirect experimental evidence, the core's
complexity, with its large size, structure and number of involved proteins, has
hindered efforts to achieve high-resolution insights and to define the roles of
the individual proteins. The specific protein composition of the core's individual
layers, including the palisade layer and the inner core wall, has remained unclear.
In this study, we have merged multiple approaches, including single particle cryo
electron microscopy of purified virus cores, cryo-electron tomography and subtomogram
averaging of mature virions and molecular modeling to elucidate the structural
determinants of the VACV core. Due to the lack of experimentally derived structures,
either in situ or reconstituted in vitro, we used Alphafold to predict models
of the putative major core protein candidates, A10, 23k, A3, A4, and L4. Our results
show that the VACV core is composed of several layers with varying local symmetries,
forming more intricate interactions than observed previously. This allowed us
to identify several molecular building blocks forming the viral core lattice.
In particular, we identified trimers of protein A10 as a major core structure
that forms the palisade layer of the viral core. Additionally, we revealed that
six petals of a flower shaped core pore within the core wall are composed of A10
trimers. Furthermore, we obtained a cryo-EM density for the inner core wall that
could potentially accommodate an A3 dimer. Integrating descriptions of protein
interactions from previous studies enabled us to provide a detailed structural
model of the poxvirus core wall, and our findings indicate that the interactions
within A10 trimers are likely consistent across orthopox- and parapoxviruses.
This combined application of cryo-SPA and cryo-ET can help overcome obstacles
in studying complex virus structures in the future, including their key assembly
proteins, interactions, and the formation into a core lattice. Our work provides
important fundamental new insights into poxvirus core architecture, also considering
the recent re-emergence of poxviruses.
acknowledged_ssus:
- _id: EM-Fac
- _id: LifeSc
- _id: ScienComp
acknowledgement: "This work was funded by the Austrian Science Fund (FWF) grant P31445
and ISTA. I\r\nwould like to express my gratitude to the Scientific Service Units,
particularly the Lab\r\nSupport Facility, the Scientific Computing Facility and
the Electron Microscopy Facility\r\nfor their tremendous support. I want to especially
thank Alois for assisting me with the\r\ninstallation of countless new software
and for troubleshooting cluster issues. A special\r\nthanks goes to Valentin for
his outstanding support in cryo-EM data acquisition and\r\nhis ongoing help in improving
the process to ensure that I obtained the best possible\r\ndata from my sample."
alternative_title:
- ISTA thesis
article_processing_charge: No
author:
- first_name: Julia
full_name: Datler, Julia
id: 3B12E2E6-F248-11E8-B48F-1D18A9856A87
last_name: Datler
orcid: 0000-0002-3616-8580
citation:
ama: Datler J. Elucidating the structural determinants of the poxvirus core using
multi-modal cryo-EM. 2024. doi:10.15479/at:ista:18766
apa: Datler, J. (2024). Elucidating the structural determinants of the poxvirus
core using multi-modal cryo-EM. Institute of Science and Technology Austria.
https://doi.org/10.15479/at:ista:18766
chicago: Datler, Julia. “Elucidating the Structural Determinants of the Poxvirus
Core Using Multi-Modal Cryo-EM.” Institute of Science and Technology Austria,
2024. https://doi.org/10.15479/at:ista:18766.
ieee: J. Datler, “Elucidating the structural determinants of the poxvirus core using
multi-modal cryo-EM,” Institute of Science and Technology Austria, 2024.
ista: Datler J. 2024. Elucidating the structural determinants of the poxvirus core
using multi-modal cryo-EM. Institute of Science and Technology Austria.
mla: Datler, Julia. Elucidating the Structural Determinants of the Poxvirus Core
Using Multi-Modal Cryo-EM. Institute of Science and Technology Austria, 2024,
doi:10.15479/at:ista:18766.
short: J. Datler, Elucidating the Structural Determinants of the Poxvirus Core Using
Multi-Modal Cryo-EM, Institute of Science and Technology Austria, 2024.
corr_author: '1'
date_created: 2025-01-07T10:23:12Z
date_published: 2024-12-30T00:00:00Z
date_updated: 2026-04-07T12:59:44Z
day: '30'
ddc:
- '570'
degree_awarded: PhD
department:
- _id: GradSch
- _id: FlSc
doi: 10.15479/at:ista:18766
file:
- access_level: closed
checksum: 3e51cab327c754045c3d29c1a50cc9a9
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has_accepted_license: '1'
keyword:
- cryo-EM
- cryo-ET
- cryo-SPA
- Structural Virology
- Poxvirus
- Vaccinia Virus
- Structural Biology
language:
- iso: eng
license: https://creativecommons.org/licenses/by-nc-nd/4.0/
month: '12'
oa: 1
oa_version: Published Version
page: '106'
project:
- _id: 26736D6A-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P31445
name: Structural conservation and diversity in retroviral capsid
publication_identifier:
isbn:
- 978-3-99078-049-7
issn:
- 2663-337X
publication_status: published
publisher: Institute of Science and Technology Austria
related_material:
record:
- id: '12334'
relation: part_of_dissertation
status: public
- id: '14979'
relation: part_of_dissertation
status: public
status: public
supervisor:
- first_name: Florian KM
full_name: Schur, Florian KM
id: 48AD8942-F248-11E8-B48F-1D18A9856A87
last_name: Schur
orcid: 0000-0003-4790-8078
title: Elucidating the structural determinants of the poxvirus core using multi-modal
cryo-EM
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legal_code_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode
name: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
(CC BY-NC-ND 4.0)
short: CC BY-NC-ND (4.0)
type: dissertation
user_id: ba8df636-2132-11f1-aed0-ed93e2281fdd
year: '2024'
...
---
DOAJ_listed: '1'
OA_place: publisher
OA_type: gold
_id: '18779'
abstract:
- lang: eng
text: Unsupervised segmentation in biological and non-biological images is only
partially resolved. Segmentation either requires arbitrary thresholds or large
teaching datasets. Here, we propose a spatial autocorrelation method based on
Local Moran’s I coefficient to differentiate signal,
background, and noise in any type of image. The method, originally described for
geoinformatics, does not require a predefined intensity threshold or teaching
algorithm for image segmentation and allows quantitative comparison of samples
obtained in different conditions. It utilizes relative intensity as well as spatial
information of neighboring elements to select spatially contiguous groups of pixels.
We demonstrate that Moran’s method outperforms threshold-based method in both
artificially generated as well as in natural images especially when background
noise is substantial. This superior performance can be attributed to the exclusion
of false positive pixels resulting from isolated, high intensity pixels in high
noise conditions. To test the method’s power in real situation, we used high power
confocal images of the somatosensory thalamus immunostained for Kv4.2 and Kv4.3
(A-type) voltage-gated potassium channels in mice. Moran’s method identified high-intensity
Kv4.2 and Kv4.3 ion channel clusters in the thalamic neuropil. Spatial distribution
of these clusters displayed strong correlation with large sensory axon terminals
of subcortical origin. The unique association of the special presynaptic terminals
and a postsynaptic voltage-gated ion channel cluster was confirmed with electron
microscopy. These data demonstrate that Moran’s method is a rapid, simple image
segmentation method optimal for variable and high noise conditions.
acknowledgement: "This research was supported by the Wellcome Trust (ZN, LA). In addition,
LA was supported by an ERC Advanced Grant (FRONTHAL, 742595) and the European Union
project RRF-2.3.1-\r\n21-2022-00004 within the framework of the Artificial Intelligence
National Laboratory and Lendület_2023_90. ZN is the recipient of a Hungarian Academy
of Sciences Momentum Grant (Lendület, LP2012-29) and an ERC Advanced Grant (293681).
We thank the Light Microscopy Center at Institute of Experimental Medicine for kindly
providing microscopy support. Authors would like to express their deepest gratitude
to Prof Luc Anselin (Center for Spatial Data Science, University of Chicago) and
Dr Szabolcs Káli (Instiute of Experimental Medicine, Budapest) for the valuable
discussion about analysis of spatial association, and to Krisztina Faddi for the
excellent technical assistance. "
article_number: '89361'
article_processing_charge: Yes
article_type: original
author:
- first_name: Csaba
full_name: Dávid, Csaba
last_name: Dávid
- first_name: Kristóf
full_name: Giber, Kristóf
last_name: Giber
- first_name: Margit Katalin
full_name: Szigeti, Margit Katalin
id: 44F4BDC0-F248-11E8-B48F-1D18A9856A87
last_name: Szigeti
orcid: 0000-0001-9500-8758
- first_name: Mihály
full_name: Köllő, Mihály
last_name: Köllő
- first_name: Zoltan
full_name: Nusser, Zoltan
last_name: Nusser
- first_name: Laszlo
full_name: Acsady, Laszlo
last_name: Acsady
citation:
ama: Dávid C, Giber K, Szigeti MK, Köllő M, Nusser Z, Acsady L. A novel image segmentation
method based on spatial autocorrelation identifies A-type potassium channel clusters
in the thalamus. eLife. 2024;12. doi:10.7554/elife.89361
apa: Dávid, C., Giber, K., Szigeti, M. K., Köllő, M., Nusser, Z., & Acsady,
L. (2024). A novel image segmentation method based on spatial autocorrelation
identifies A-type potassium channel clusters in the thalamus. ELife. eLife
Sciences Publications. https://doi.org/10.7554/elife.89361
chicago: Dávid, Csaba, Kristóf Giber, Margit Katalin Szigeti, Mihály Köllő, Zoltan
Nusser, and Laszlo Acsady. “A Novel Image Segmentation Method Based on Spatial
Autocorrelation Identifies A-Type Potassium Channel Clusters in the Thalamus.”
ELife. eLife Sciences Publications, 2024. https://doi.org/10.7554/elife.89361.
ieee: C. Dávid, K. Giber, M. K. Szigeti, M. Köllő, Z. Nusser, and L. Acsady, “A
novel image segmentation method based on spatial autocorrelation identifies A-type
potassium channel clusters in the thalamus,” eLife, vol. 12. eLife Sciences
Publications, 2024.
ista: Dávid C, Giber K, Szigeti MK, Köllő M, Nusser Z, Acsady L. 2024. A novel image
segmentation method based on spatial autocorrelation identifies A-type potassium
channel clusters in the thalamus. eLife. 12, 89361.
mla: Dávid, Csaba, et al. “A Novel Image Segmentation Method Based on Spatial Autocorrelation
Identifies A-Type Potassium Channel Clusters in the Thalamus.” ELife, vol.
12, 89361, eLife Sciences Publications, 2024, doi:10.7554/elife.89361.
short: C. Dávid, K. Giber, M.K. Szigeti, M. Köllő, Z. Nusser, L. Acsady, ELife 12
(2024).
date_created: 2025-01-08T13:25:45Z
date_published: 2024-12-10T00:00:00Z
date_updated: 2025-01-08T13:37:04Z
day: '10'
ddc:
- '570'
department:
- _id: GaNo
doi: 10.7554/elife.89361
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checksum: 1d64265f62a3bf14550b4f5c684f1782
content_type: application/pdf
creator: dernst
date_created: 2025-01-08T13:33:05Z
date_updated: 2025-01-08T13:33:05Z
file_id: '18780'
file_name: 2024_eLife_David.pdf
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success: 1
file_date_updated: 2025-01-08T13:33:05Z
has_accepted_license: '1'
intvolume: ' 12'
language:
- iso: eng
month: '12'
oa: 1
oa_version: Published Version
publication: eLife
publication_identifier:
issn:
- 2050-084X
publication_status: published
publisher: eLife Sciences Publications
quality_controlled: '1'
scopus_import: '1'
status: public
title: A novel image segmentation method based on spatial autocorrelation identifies
A-type potassium channel clusters in the thalamus
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
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year: '2024'
...
---
OA_place: publisher
OA_type: gold
_id: '18847'
abstract:
- lang: eng
text: "Machine Learning and AI have the potential to transform data-driven\r\nscientific
discovery, enabling accurate predictions for several scientific\r\nphenomena.
As many scientific questions are inherently causal, this paper looks\r\nat the
causal inference task of treatment effect estimation, where the outcome\r\nof
interest is recorded in high-dimensional observations in a Randomized\r\nControlled
Trial (RCT). Despite being the simplest possible causal setting and\r\na perfect
fit for deep learning, we theoretically find that many common choices\r\nin the
literature may lead to biased estimates. To test the practical impact of\r\nthese
considerations, we recorded ISTAnt, the first real-world benchmark for\r\ncausal
inference downstream tasks on high-dimensional observations as an RCT\r\nstudying
how garden ants (Lasius neglectus) respond to microparticles applied\r\nonto their
colony members by hygienic grooming. Comparing 6 480 models\r\nfine-tuned from
state-of-the-art visual backbones, we find that the sampling\r\nand modeling choices
significantly affect the accuracy of the causal estimate,\r\nand that classification
accuracy is not a proxy thereof. We further validated\r\nthe analysis, repeating
it on a synthetically generated visual data set\r\ncontrolling the causal model.
Our results suggest that future benchmarks should\r\ncarefully consider real downstream
scientific questions, especially causal\r\nones. Further, we highlight guidelines
for representation learning methods to\r\nhelp answer causal questions in the
sciences."
acknowledgement: We thank Piersilvio De Bartolomeis, and the full Causal Learning
and Artificial Intelligence (CLAI) group at ISTA for the extremely helpful discussions.
Riccardo Cadei was supported by a Google Research Scholar Award and a Google Initiated
Gift to Francesco Locatello. We thank the Social Immunity team at ISTA particularly
Michaela Hönigsberger and Wilfrid Jean Louis, for supporting the ecological experiment
and Farnaz Beikzadeh Abbasi, Luisa Fiebig and Martin Estermann for annotating ant
behavior in ISTAnt.
article_processing_charge: No
arxiv: 1
author:
- first_name: Riccardo
full_name: Cadei, Riccardo
id: 0fa8b76f-72f0-11ef-b75a-a5da96e5ad6b
last_name: Cadei
- first_name: Lukas
full_name: Lindorfer, Lukas
id: 85f0e6d3-06b3-11ec-8982-8c5049fa4455
last_name: Lindorfer
- first_name: Sylvia
full_name: Cremer, Sylvia
id: 2F64EC8C-F248-11E8-B48F-1D18A9856A87
last_name: Cremer
orcid: 0000-0002-2193-3868
- first_name: Cordelia
full_name: Schmid, Cordelia
last_name: Schmid
- first_name: Francesco
full_name: Locatello, Francesco
id: 26cfd52f-2483-11ee-8040-88983bcc06d4
last_name: Locatello
orcid: 0000-0002-4850-0683
citation:
ama: 'Cadei R, Lindorfer L, Cremer S, Schmid C, Locatello F. Smoke and mirrors in
causal downstream tasks. In: ICML 2024 Workshop AI4Science. Vol 38. Curran
Associates; 2024.'
apa: Cadei, R., Lindorfer, L., Cremer, S., Schmid, C., & Locatello, F. (2024).
Smoke and mirrors in causal downstream tasks. In ICML 2024 Workshop AI4Science
(Vol. 38). Curran Associates.
chicago: Cadei, Riccardo, Lukas Lindorfer, Sylvia Cremer, Cordelia Schmid, and Francesco
Locatello. “Smoke and Mirrors in Causal Downstream Tasks.” In ICML 2024 Workshop
AI4Science, Vol. 38. Curran Associates, 2024.
ieee: R. Cadei, L. Lindorfer, S. Cremer, C. Schmid, and F. Locatello, “Smoke and
mirrors in causal downstream tasks,” in ICML 2024 Workshop AI4Science,
2024, vol. 38.
ista: 'Cadei R, Lindorfer L, Cremer S, Schmid C, Locatello F. 2024. Smoke and mirrors
in causal downstream tasks. ICML 2024 Workshop AI4Science. ICML: International
Conference on Machine Learning vol. 38.'
mla: Cadei, Riccardo, et al. “Smoke and Mirrors in Causal Downstream Tasks.” ICML
2024 Workshop AI4Science, vol. 38, Curran Associates, 2024.
short: R. Cadei, L. Lindorfer, S. Cremer, C. Schmid, F. Locatello, in:, ICML 2024
Workshop AI4Science, Curran Associates, 2024.
conference:
end_date: 2024-07-26
name: 'ICML: International Conference on Machine Learning'
start_date: 2024-07-26
corr_author: '1'
date_created: 2025-01-14T07:27:26Z
date_published: 2024-09-25T00:00:00Z
date_updated: 2025-07-10T11:51:50Z
day: '25'
ddc:
- '000'
- '570'
department:
- _id: SyCr
- _id: FrLo
- _id: GradSch
external_id:
arxiv:
- '2405.17151'
file:
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creator: dernst
date_created: 2025-01-27T11:42:24Z
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file_date_updated: 2025-01-27T11:42:24Z
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publication: ICML 2024 Workshop AI4Science
publication_status: published
publisher: Curran Associates
quality_controlled: '1'
related_material:
link:
- relation: software
url: https://github.com/CausalLearningAI/ISTAnt
record:
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relation: research_data
status: public
- id: '19509'
relation: is_continued_by
status: for_moderation
scopus_import: '1'
status: public
title: Smoke and mirrors in causal downstream tasks
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: 38
year: '2024'
...
---
DOAJ_listed: '1'
OA_place: publisher
OA_type: gold
_id: '18856'
abstract:
- lang: eng
text: This research is aimed to solve the tweet/user geolocation prediction task
and provide a flexible methodology for the geo-tagging of textual big data. The
suggested approach implements neural networks for natural language processing
(NLP) to estimate the location as coordinate pairs (longitude, latitude) and two-dimensional
Gaussian Mixture Models (GMMs). The scope of proposed models has been finetuned
on a Twitter dataset using pretrained Bidirectional Encoder Representations from
Transformers (BERT) as base models. Performance metrics show a median error of
fewer than 30 km on a worldwide-level, and fewer than 15 km on the US-level datasets
for the models trained and evaluated on text features of tweets' content and metadata
context. Our source code and data are available at https://github.com/K4TEL/geo-twitter.git.
acknowledgement: The authors acknowledge the Institute of Science and Technology (ISTA)
for their material support and for granting access to the Twitter database archive,
which was essential for the research.
article_processing_charge: Yes
article_type: original
author:
- first_name: Kateryna
full_name: Lutsai, Kateryna
last_name: Lutsai
- first_name: Christoph
full_name: Lampert, Christoph
id: 40C20FD2-F248-11E8-B48F-1D18A9856A87
last_name: Lampert
orcid: 0000-0001-8622-7887
citation:
ama: Lutsai K, Lampert C. Predicting the geolocation of tweets using transformer
models on customized data. Journal of Spatial Information Science. 2024;(29):69-99.
doi:10.5311/JOSIS.2024.29.295
apa: Lutsai, K., & Lampert, C. (2024). Predicting the geolocation of tweets
using transformer models on customized data. Journal of Spatial Information
Science. University of Maine. https://doi.org/10.5311/JOSIS.2024.29.295
chicago: Lutsai, Kateryna, and Christoph Lampert. “Predicting the Geolocation of
Tweets Using Transformer Models on Customized Data.” Journal of Spatial Information
Science. University of Maine, 2024. https://doi.org/10.5311/JOSIS.2024.29.295.
ieee: K. Lutsai and C. Lampert, “Predicting the geolocation of tweets using transformer
models on customized data,” Journal of Spatial Information Science, no.
29. University of Maine, pp. 69–99, 2024.
ista: Lutsai K, Lampert C. 2024. Predicting the geolocation of tweets using transformer
models on customized data. Journal of Spatial Information Science. (29), 69–99.
mla: Lutsai, Kateryna, and Christoph Lampert. “Predicting the Geolocation of Tweets
Using Transformer Models on Customized Data.” Journal of Spatial Information
Science, no. 29, University of Maine, 2024, pp. 69–99, doi:10.5311/JOSIS.2024.29.295.
short: K. Lutsai, C. Lampert, Journal of Spatial Information Science (2024) 69–99.
corr_author: '1'
date_created: 2025-01-19T23:01:53Z
date_published: 2024-12-26T00:00:00Z
date_updated: 2025-06-05T13:47:12Z
day: '26'
ddc:
- '500'
department:
- _id: ChLa
doi: 10.5311/JOSIS.2024.29.295
file:
- access_level: open_access
checksum: b82413f00398ffb5168e8e747571a98d
content_type: application/pdf
creator: dernst
date_created: 2025-01-20T08:41:10Z
date_updated: 2025-01-20T08:41:10Z
file_id: '18857'
file_name: 2024_JourSpatialInfoScience_Lutsai.pdf
file_size: 7250655
relation: main_file
success: 1
file_date_updated: 2025-01-20T08:41:10Z
has_accepted_license: '1'
issue: '29'
language:
- iso: eng
license: https://creativecommons.org/licenses/by/3.0/
month: '12'
oa: 1
oa_version: Published Version
page: 69-99
publication: Journal of Spatial Information Science
publication_identifier:
eissn:
- 1948-660X
publication_status: published
publisher: University of Maine
quality_controlled: '1'
related_material:
link:
- relation: software
url: https://github.com/K4TEL/geo-twitter.git
scopus_import: '1'
status: public
title: Predicting the geolocation of tweets using transformer models on customized
data
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/3.0/legalcode
name: Creative Commons Attribution 3.0 Unported (CC BY 3.0)
short: CC BY (3.0)
type: journal_article
user_id: 68b8ca59-c5b3-11ee-8790-cd641c68093d
year: '2024'
...
---
OA_type: closed access
_id: '18867'
abstract:
- lang: eng
text: 'In an accreting X-ray pulsar, a neutron star accretes matter from a companion
star through an accretion disk. The magnetic field of the rotating neutron star
disrupts the inner edge of the disk, funnelling the gas to flow onto the poles
on its surface. Hercules X-1 is a prototypical persistent X-ray pulsar about 7 kpc
from Earth. Its emission varies on three distinct timescales: the neutron star
rotates every 1.2 s, it is eclipsed by its companion each 1.7 d, and the system
exhibits a superorbital period of 35 d, which has remained stable since its discovery.
Several lines of evidence point to the source of this variation as the precession
of the accretion disk or that of the neutron star. Despite the many hints over
the past 50 yr, the precession of the neutron star itself has yet not been confirmed
or refuted. X-ray polarization measurements (probing the spin geometry of Her
X-1) with the Imaging X-ray Polarimetry Explorer suggest that free precession
of the neutron star crust sets the 35 d period; this has the important implication
that its crust is somewhat asymmetric by a few parts per ten million.'
article_processing_charge: No
article_type: original
author:
- first_name: Jeremy
full_name: Heyl, Jeremy
last_name: Heyl
- first_name: Victor
full_name: Doroshenko, Victor
last_name: Doroshenko
- first_name: Denis
full_name: González-Caniulef, Denis
last_name: González-Caniulef
- first_name: Ilaria
full_name: Caiazzo, Ilaria
id: 8ae5b6e7-2a03-11ee-914d-b58ed7a3b47d
last_name: Caiazzo
orcid: 0000-0002-4770-5388
- first_name: Juri
full_name: Poutanen, Juri
last_name: Poutanen
- first_name: Alexander
full_name: Mushtukov, Alexander
last_name: Mushtukov
- first_name: Sergey S.
full_name: Tsygankov, Sergey S.
last_name: Tsygankov
- first_name: Demet
full_name: Kirmizibayrak, Demet
last_name: Kirmizibayrak
- first_name: Matteo
full_name: Bachetti, Matteo
last_name: Bachetti
- first_name: George G.
full_name: Pavlov, George G.
last_name: Pavlov
- first_name: Sofia V.
full_name: Forsblom, Sofia V.
last_name: Forsblom
- first_name: Christian
full_name: Malacaria, Christian
last_name: Malacaria
- first_name: Valery F.
full_name: Suleimanov, Valery F.
last_name: Suleimanov
- first_name: Iván
full_name: Agudo, Iván
last_name: Agudo
- first_name: Lucio Angelo
full_name: Antonelli, Lucio Angelo
last_name: Antonelli
- first_name: Luca
full_name: Baldini, Luca
last_name: Baldini
- first_name: Wayne H.
full_name: Baumgartner, Wayne H.
last_name: Baumgartner
- first_name: Ronaldo
full_name: Bellazzini, Ronaldo
last_name: Bellazzini
- first_name: Stefano
full_name: Bianchi, Stefano
last_name: Bianchi
- first_name: Stephen D.
full_name: Bongiorno, Stephen D.
last_name: Bongiorno
- first_name: Raffaella
full_name: Bonino, Raffaella
last_name: Bonino
- first_name: Alessandro
full_name: Brez, Alessandro
last_name: Brez
- first_name: Niccolò
full_name: Bucciantini, Niccolò
last_name: Bucciantini
- first_name: Fiamma
full_name: Capitanio, Fiamma
last_name: Capitanio
- first_name: Simone
full_name: Castellano, Simone
last_name: Castellano
- first_name: Elisabetta
full_name: Cavazzuti, Elisabetta
last_name: Cavazzuti
- first_name: Chien-Ting
full_name: Chen, Chien-Ting
last_name: Chen
- first_name: Stefano
full_name: Ciprini, Stefano
last_name: Ciprini
- first_name: Enrico
full_name: Costa, Enrico
last_name: Costa
- first_name: Alessandra
full_name: De Rosa, Alessandra
last_name: De Rosa
- first_name: Ettore
full_name: Del Monte, Ettore
last_name: Del Monte
- first_name: Laura
full_name: Di Gesu, Laura
last_name: Di Gesu
- first_name: Niccolò
full_name: Di Lalla, Niccolò
last_name: Di Lalla
- first_name: Alessandro
full_name: Di Marco, Alessandro
last_name: Di Marco
- first_name: Immacolata
full_name: Donnarumma, Immacolata
last_name: Donnarumma
- first_name: Michal
full_name: Dovčiak, Michal
last_name: Dovčiak
- first_name: Steven R.
full_name: Ehlert, Steven R.
last_name: Ehlert
- first_name: Teruaki
full_name: Enoto, Teruaki
last_name: Enoto
- first_name: Yuri
full_name: Evangelista, Yuri
last_name: Evangelista
- first_name: Sergio
full_name: Fabiani, Sergio
last_name: Fabiani
- first_name: Riccardo
full_name: Ferrazzoli, Riccardo
last_name: Ferrazzoli
- first_name: Javier A.
full_name: Garcia, Javier A.
last_name: Garcia
- first_name: Shuichi
full_name: Gunji, Shuichi
last_name: Gunji
- first_name: Kiyoshi
full_name: Hayashida, Kiyoshi
last_name: Hayashida
- first_name: Wataru
full_name: Iwakiri, Wataru
last_name: Iwakiri
- first_name: Svetlana G.
full_name: Jorstad, Svetlana G.
last_name: Jorstad
- first_name: Philip
full_name: Kaaret, Philip
last_name: Kaaret
- first_name: Vladimir
full_name: Karas, Vladimir
last_name: Karas
- first_name: Fabian
full_name: Kislat, Fabian
last_name: Kislat
- first_name: Takao
full_name: Kitaguchi, Takao
last_name: Kitaguchi
- first_name: Jeffery J.
full_name: Kolodziejczak, Jeffery J.
last_name: Kolodziejczak
- first_name: Henric
full_name: Krawczynski, Henric
last_name: Krawczynski
- first_name: Fabio
full_name: La Monaca, Fabio
last_name: La Monaca
- first_name: Luca
full_name: Latronico, Luca
last_name: Latronico
- first_name: Ioannis
full_name: Liodakis, Ioannis
last_name: Liodakis
- first_name: Simone
full_name: Maldera, Simone
last_name: Maldera
- first_name: Alberto
full_name: Manfreda, Alberto
last_name: Manfreda
- first_name: Frédéric
full_name: Marin, Frédéric
last_name: Marin
- first_name: Andrea
full_name: Marinucci, Andrea
last_name: Marinucci
- first_name: Alan P.
full_name: Marscher, Alan P.
last_name: Marscher
- first_name: Herman L.
full_name: Marshall, Herman L.
last_name: Marshall
- first_name: Francesco
full_name: Massaro, Francesco
last_name: Massaro
- first_name: Giorgio
full_name: Matt, Giorgio
last_name: Matt
- first_name: Ikuyuki
full_name: Mitsuishi, Ikuyuki
last_name: Mitsuishi
- first_name: Tsunefumi
full_name: Mizuno, Tsunefumi
last_name: Mizuno
- first_name: Fabio
full_name: Muleri, Fabio
last_name: Muleri
- first_name: Michela
full_name: Negro, Michela
last_name: Negro
- first_name: C.-Y.
full_name: Ng, C.-Y.
last_name: Ng
- first_name: Stephen L.
full_name: O’Dell, Stephen L.
last_name: O’Dell
- first_name: Nicola
full_name: Omodei, Nicola
last_name: Omodei
- first_name: Chiara
full_name: Oppedisano, Chiara
last_name: Oppedisano
- first_name: Alessandro
full_name: Papitto, Alessandro
last_name: Papitto
- first_name: Abel Lawrence
full_name: Peirson, Abel Lawrence
last_name: Peirson
- first_name: Matteo
full_name: Perri, Matteo
last_name: Perri
- first_name: Melissa
full_name: Pesce-Rollins, Melissa
last_name: Pesce-Rollins
- first_name: Pierre-Olivier
full_name: Petrucci, Pierre-Olivier
last_name: Petrucci
- first_name: Maura
full_name: Pilia, Maura
last_name: Pilia
- first_name: Andrea
full_name: Possenti, Andrea
last_name: Possenti
- first_name: Simonetta
full_name: Puccetti, Simonetta
last_name: Puccetti
- first_name: Brian D.
full_name: Ramsey, Brian D.
last_name: Ramsey
- first_name: John
full_name: Rankin, John
last_name: Rankin
- first_name: Ajay
full_name: Ratheesh, Ajay
last_name: Ratheesh
- first_name: Oliver J.
full_name: Roberts, Oliver J.
last_name: Roberts
- first_name: Roger W.
full_name: Romani, Roger W.
last_name: Romani
- first_name: Carmelo
full_name: Sgrò, Carmelo
last_name: Sgrò
- first_name: Patrick
full_name: Slane, Patrick
last_name: Slane
- first_name: Paolo
full_name: Soffitta, Paolo
last_name: Soffitta
- first_name: Gloria
full_name: Spandre, Gloria
last_name: Spandre
- first_name: Douglas A.
full_name: Swartz, Douglas A.
last_name: Swartz
- first_name: Toru
full_name: Tamagawa, Toru
last_name: Tamagawa
- first_name: Fabrizio
full_name: Tavecchio, Fabrizio
last_name: Tavecchio
- first_name: Roberto
full_name: Taverna, Roberto
last_name: Taverna
- first_name: Yuzuru
full_name: Tawara, Yuzuru
last_name: Tawara
- first_name: Allyn F.
full_name: Tennant, Allyn F.
last_name: Tennant
- first_name: Nicholas E.
full_name: Thomas, Nicholas E.
last_name: Thomas
- first_name: Francesco
full_name: Tombesi, Francesco
last_name: Tombesi
- first_name: Alessio
full_name: Trois, Alessio
last_name: Trois
- first_name: Roberto
full_name: Turolla, Roberto
last_name: Turolla
- first_name: Jacco
full_name: Vink, Jacco
last_name: Vink
- first_name: Martin C.
full_name: Weisskopf, Martin C.
last_name: Weisskopf
- first_name: Kinwah
full_name: Wu, Kinwah
last_name: Wu
- first_name: Fei
full_name: Xie, Fei
last_name: Xie
- first_name: Silvia
full_name: Zane, Silvia
last_name: Zane
citation:
ama: Heyl J, Doroshenko V, González-Caniulef D, et al. Complex rotational dynamics
of the neutron star in Hercules X-1 revealed by X-ray polarization. Nature
Astronomy. 2024;8:1047-1053. doi:10.1038/s41550-024-02295-8
apa: Heyl, J., Doroshenko, V., González-Caniulef, D., Caiazzo, I., Poutanen, J.,
Mushtukov, A., … Zane, S. (2024). Complex rotational dynamics of the neutron star
in Hercules X-1 revealed by X-ray polarization. Nature Astronomy. Springer
Nature. https://doi.org/10.1038/s41550-024-02295-8
chicago: Heyl, Jeremy, Victor Doroshenko, Denis González-Caniulef, Ilaria Caiazzo,
Juri Poutanen, Alexander Mushtukov, Sergey S. Tsygankov, et al. “Complex Rotational
Dynamics of the Neutron Star in Hercules X-1 Revealed by X-Ray Polarization.”
Nature Astronomy. Springer Nature, 2024. https://doi.org/10.1038/s41550-024-02295-8.
ieee: J. Heyl et al., “Complex rotational dynamics of the neutron star in
Hercules X-1 revealed by X-ray polarization,” Nature Astronomy, vol. 8.
Springer Nature, pp. 1047–1053, 2024.
ista: Heyl J et al. 2024. Complex rotational dynamics of the neutron star in Hercules
X-1 revealed by X-ray polarization. Nature Astronomy. 8, 1047–1053.
mla: Heyl, Jeremy, et al. “Complex Rotational Dynamics of the Neutron Star in Hercules
X-1 Revealed by X-Ray Polarization.” Nature Astronomy, vol. 8, Springer
Nature, 2024, pp. 1047–53, doi:10.1038/s41550-024-02295-8.
short: J. Heyl, V. Doroshenko, D. González-Caniulef, I. Caiazzo, J. Poutanen, A.
Mushtukov, S.S. Tsygankov, D. Kirmizibayrak, M. Bachetti, G.G. Pavlov, S.V. Forsblom,
C. Malacaria, V.F. Suleimanov, I. Agudo, L.A. Antonelli, L. Baldini, W.H. Baumgartner,
R. Bellazzini, S. Bianchi, S.D. Bongiorno, R. Bonino, A. Brez, N. Bucciantini,
F. Capitanio, S. Castellano, E. Cavazzuti, C.-T. Chen, S. Ciprini, E. Costa, A.
De Rosa, E. Del Monte, L. Di Gesu, N. Di Lalla, A. Di Marco, I. Donnarumma, M.
Dovčiak, S.R. Ehlert, T. Enoto, Y. Evangelista, S. Fabiani, R. Ferrazzoli, J.A.
Garcia, S. Gunji, K. Hayashida, W. Iwakiri, S.G. Jorstad, P. Kaaret, V. Karas,
F. Kislat, T. Kitaguchi, J.J. Kolodziejczak, H. Krawczynski, F. La Monaca, L.
Latronico, I. Liodakis, S. Maldera, A. Manfreda, F. Marin, A. Marinucci, A.P.
Marscher, H.L. Marshall, F. Massaro, G. Matt, I. Mitsuishi, T. Mizuno, F. Muleri,
M. Negro, C.-Y. Ng, S.L. O’Dell, N. Omodei, C. Oppedisano, A. Papitto, A.L. Peirson,
M. Perri, M. Pesce-Rollins, P.-O. Petrucci, M. Pilia, A. Possenti, S. Puccetti,
B.D. Ramsey, J. Rankin, A. Ratheesh, O.J. Roberts, R.W. Romani, C. Sgrò, P. Slane,
P. Soffitta, G. Spandre, D.A. Swartz, T. Tamagawa, F. Tavecchio, R. Taverna, Y.
Tawara, A.F. Tennant, N.E. Thomas, F. Tombesi, A. Trois, R. Turolla, J. Vink,
M.C. Weisskopf, K. Wu, F. Xie, S. Zane, Nature Astronomy 8 (2024) 1047–1053.
date_created: 2025-01-21T15:35:17Z
date_published: 2024-08-01T00:00:00Z
date_updated: 2025-01-27T10:52:16Z
day: '01'
doi: 10.1038/s41550-024-02295-8
extern: '1'
intvolume: ' 8'
language:
- iso: eng
month: '08'
oa_version: None
page: 1047-1053
publication: Nature Astronomy
publication_identifier:
issn:
- 2397-3366
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: Complex rotational dynamics of the neutron star in Hercules X-1 revealed by
X-ray polarization
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 8
year: '2024'
...
---
DOAJ_listed: '1'
OA_place: publisher
OA_type: gold
_id: '18868'
abstract:
- lang: eng
text: We develop two new highly efficient estimators to measure the polarization
(Stokes parameters) in experiments that constrain the position angle of individual
photons such as scattering and gas-pixel-detector polarimeters, and analyse in
detail a previously proposed estimator. All three of these estimators are at least
fifty percent more efficient on typical datasets than the standard estimator used
in the field. We present analytic estimates of the variance of these estimators
and numerical experiments to verify these estimates. Two of the three estimators
can be calculated quickly and directly through summations over the measurements
of individual photons.
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Jeremy
full_name: Heyl, Jeremy
last_name: Heyl
- first_name: Denis
full_name: González-Caniulef, Denis
last_name: González-Caniulef
- first_name: Ilaria
full_name: Caiazzo, Ilaria
id: 8ae5b6e7-2a03-11ee-914d-b58ed7a3b47d
last_name: Caiazzo
orcid: 0000-0002-4770-5388
citation:
ama: Heyl J, González-Caniulef D, Caiazzo I. Optimal summary statistics for X-ray
polarization. The Open Journal of Astrophysics. 2024;7. doi:10.33232/001c.117476
apa: Heyl, J., González-Caniulef, D., & Caiazzo, I. (2024). Optimal summary
statistics for X-ray polarization. The Open Journal of Astrophysics. Maynooth
Academic Publishing. https://doi.org/10.33232/001c.117476
chicago: Heyl, Jeremy, Denis González-Caniulef, and Ilaria Caiazzo. “Optimal Summary
Statistics for X-Ray Polarization.” The Open Journal of Astrophysics. Maynooth
Academic Publishing, 2024. https://doi.org/10.33232/001c.117476.
ieee: J. Heyl, D. González-Caniulef, and I. Caiazzo, “Optimal summary statistics
for X-ray polarization,” The Open Journal of Astrophysics, vol. 7. Maynooth
Academic Publishing, 2024.
ista: Heyl J, González-Caniulef D, Caiazzo I. 2024. Optimal summary statistics for
X-ray polarization. The Open Journal of Astrophysics. 7.
mla: Heyl, Jeremy, et al. “Optimal Summary Statistics for X-Ray Polarization.” The
Open Journal of Astrophysics, vol. 7, Maynooth Academic Publishing, 2024,
doi:10.33232/001c.117476.
short: J. Heyl, D. González-Caniulef, I. Caiazzo, The Open Journal of Astrophysics
7 (2024).
date_created: 2025-01-21T15:54:16Z
date_published: 2024-05-01T00:00:00Z
date_updated: 2025-01-27T10:48:19Z
day: '01'
doi: 10.33232/001c.117476
extern: '1'
external_id:
arxiv:
- '2311.07805'
intvolume: ' 7'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.33232/001c.117476
month: '05'
oa: 1
oa_version: Published Version
publication: The Open Journal of Astrophysics
publication_identifier:
issn:
- 2565-6120
publication_status: published
publisher: Maynooth Academic Publishing
quality_controlled: '1'
scopus_import: '1'
status: public
title: Optimal summary statistics for X-ray polarization
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 7
year: '2024'
...
---
OA_place: publisher
OA_type: gold
_id: '18875'
abstract:
- lang: eng
text: Current state-of-the-art methods for differentially private model training
are based on matrix factorization techniques. However, these methods suffer from
high computational overhead because they require numerically solving a demanding
optimization problem to determine an approximately optimal factorization prior
to the actual model training. In this work, we present a new matrix factorization
approach, BSR, which overcomes this computational bottleneck. By exploiting properties
of the standard matrix square root, BSR allows to efficiently handle also large-scale
problems. For the key scenario of stochastic gradient descent with momentum and
weight decay, we even derive analytical expressions for BSR that render the computational
overhead negligible. We prove bounds on the approximation quality that hold both
in the centralized and in the federated learning setting. Our numerical experiments
demonstrate that models trained using BSR perform on par with the best existing
methods, while completely avoiding their computational overhead.
alternative_title:
- Advances in Neural Information Processing Systems
article_processing_charge: No
arxiv: 1
author:
- first_name: Nikita
full_name: Kalinin, Nikita
id: 4b14526e-14d2-11ed-ba64-c14c9553d137
last_name: Kalinin
- first_name: Christoph
full_name: Lampert, Christoph
id: 40C20FD2-F248-11E8-B48F-1D18A9856A87
last_name: Lampert
orcid: 0000-0001-8622-7887
citation:
ama: 'Kalinin N, Lampert C. Banded square root matrix factorization for differentially
private model training. In: 38th Annual Conference on Neural Information Processing
Systems. Vol 37. Neural Information Processing Systems Foundation; 2024.'
apa: 'Kalinin, N., & Lampert, C. (2024). Banded square root matrix factorization
for differentially private model training. In 38th Annual Conference on Neural
Information Processing Systems (Vol. 37). Vancouver, Canada: Neural Information
Processing Systems Foundation.'
chicago: Kalinin, Nikita, and Christoph Lampert. “Banded Square Root Matrix Factorization
for Differentially Private Model Training.” In 38th Annual Conference on Neural
Information Processing Systems, Vol. 37. Neural Information Processing Systems
Foundation, 2024.
ieee: N. Kalinin and C. Lampert, “Banded square root matrix factorization for differentially
private model training,” in 38th Annual Conference on Neural Information Processing
Systems, Vancouver, Canada, 2024, vol. 37.
ista: 'Kalinin N, Lampert C. 2024. Banded square root matrix factorization for differentially
private model training. 38th Annual Conference on Neural Information Processing
Systems. NeurIPS: Neural Information Processing Systems, Advances in Neural Information
Processing Systems, vol. 37.'
mla: Kalinin, Nikita, and Christoph Lampert. “Banded Square Root Matrix Factorization
for Differentially Private Model Training.” 38th Annual Conference on Neural
Information Processing Systems, vol. 37, Neural Information Processing Systems
Foundation, 2024.
short: N. Kalinin, C. Lampert, in:, 38th Annual Conference on Neural Information
Processing Systems, Neural Information Processing Systems Foundation, 2024.
conference:
end_date: 2024-12-16
location: Vancouver, Canada
name: 'NeurIPS: Neural Information Processing Systems'
start_date: 2024-12-16
corr_author: '1'
date_created: 2025-01-24T17:58:16Z
date_published: 2024-12-01T00:00:00Z
date_updated: 2025-05-14T11:34:20Z
day: '01'
ddc:
- '000'
department:
- _id: GradSch
- _id: ChLa
external_id:
arxiv:
- '2405.13763'
file:
- access_level: open_access
checksum: a216cab8eddc1fe7840aede0e2c0d41e
content_type: application/pdf
creator: dernst
date_created: 2025-01-27T09:52:15Z
date_updated: 2025-01-27T09:52:15Z
file_id: '18888'
file_name: 2024_NeurIPS_Nikita.pdf
file_size: 1144656
relation: main_file
success: 1
file_date_updated: 2025-01-27T09:52:15Z
has_accepted_license: '1'
intvolume: ' 37'
language:
- iso: eng
month: '12'
oa: 1
oa_version: Published Version
publication: 38th Annual Conference on Neural Information Processing Systems
publication_identifier:
eissn:
- 1049-5258
publication_status: published
publisher: Neural Information Processing Systems Foundation
quality_controlled: '1'
scopus_import: '1'
status: public
title: Banded square root matrix factorization for differentially private model training
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: 37
year: '2024'
...
---
OA_place: repository
OA_type: green
_id: '18890'
abstract:
- lang: eng
text: Deep Neural Collapse (DNC) refers to the surprisingly rigid structure of the
data representations in the final layers of Deep Neural Networks (DNNs). Though
the phenomenon has been measured in a variety of settings, its emergence is typically
explained via data-agnostic approaches, such as the unconstrained features model.
In this work, we introduce a data-dependent setting where DNC forms due to feature
learning through the average gradient outer product (AGOP). The AGOP is defined
with respect to a learned predictor and is equal to the uncentered covariance
matrix of its input-output gradients averaged over the training dataset. The Deep
Recursive Feature Machine (Deep RFM) is a method that constructs a neural network
by iteratively mapping the data with the AGOP and applying an untrained random
feature map. We demonstrate empirically that DNC occurs in Deep RFM across standard
settings as a consequence of the projection with the AGOP matrix computed at each
layer. Further, we theoretically explain DNC in Deep RFM in an asymptotic setting
and as a result of kernel learning. We then provide evidence that this mechanism
holds for neural networks more generally. In particular, we show that the right
singular vectors and values of the weights can be responsible for the majority
of within-class variability collapse for DNNs trained in the feature learning
regime. As observed in recent work, this singular structure is highly correlated
with that of the AGOP.
acknowledgement: 'We acknowledge support from the National Science Foundation (NSF)
and the Simons Foundation for the Collaboration on the Theoretical Foundations of
Deep Learning through awards DMS-2031883 and #814639 as well as the TILOS institute
(NSF CCF-2112665). This work used the programs (1) XSEDE (Extreme science and engineering
discovery environment) which is supported by NSF grant numbers ACI-1548562, and
(2) ACCESS (Advanced cyberinfrastructure coordination ecosystem: services & support)
which is supported by NSF grants numbers #2138259, #2138286, #2138307, #2137603,
and #2138296. Specifically, we used the resources from SDSC Expanse GPU compute
nodes, and NCSA Delta system, via allocations TG-CIS220009. Marco Mondelli is supported
by the 2019 Lopez-Loreta prize. We also acknowledge useful feedback from anonymous
reviewers. '
alternative_title:
- Advances in Neural Information Processing Systems
article_processing_charge: No
arxiv: 1
author:
- first_name: Daniel
full_name: Beaglehole, Daniel
last_name: Beaglehole
- first_name: Peter
full_name: Súkeník, Peter
id: d64d6a8d-eb8e-11eb-b029-96fd216dec3c
last_name: Súkeník
- first_name: Marco
full_name: Mondelli, Marco
id: 27EB676C-8706-11E9-9510-7717E6697425
last_name: Mondelli
orcid: 0000-0002-3242-7020
- first_name: Mikhail
full_name: Belkin, Mikhail
last_name: Belkin
citation:
ama: 'Beaglehole D, Súkeník P, Mondelli M, Belkin M. Average gradient outer product
as a mechanism for deep neural collapse. In: 38th Annual Conference on Neural
Information Processing Systems. Vol 37. Neural Information Processing Systems
Foundation; 2024.'
apa: 'Beaglehole, D., Súkeník, P., Mondelli, M., & Belkin, M. (2024). Average
gradient outer product as a mechanism for deep neural collapse. In 38th Annual
Conference on Neural Information Processing Systems (Vol. 37). Vancouver,
Canada: Neural Information Processing Systems Foundation.'
chicago: Beaglehole, Daniel, Peter Súkeník, Marco Mondelli, and Mikhail Belkin.
“Average Gradient Outer Product as a Mechanism for Deep Neural Collapse.” In 38th
Annual Conference on Neural Information Processing Systems, Vol. 37. Neural
Information Processing Systems Foundation, 2024.
ieee: D. Beaglehole, P. Súkeník, M. Mondelli, and M. Belkin, “Average gradient outer
product as a mechanism for deep neural collapse,” in 38th Annual Conference
on Neural Information Processing Systems, Vancouver, Canada, 2024, vol. 37.
ista: 'Beaglehole D, Súkeník P, Mondelli M, Belkin M. 2024. Average gradient outer
product as a mechanism for deep neural collapse. 38th Annual Conference on Neural
Information Processing Systems. NeurIPS: Neural Information Processing Systems,
Advances in Neural Information Processing Systems, vol. 37.'
mla: Beaglehole, Daniel, et al. “Average Gradient Outer Product as a Mechanism for
Deep Neural Collapse.” 38th Annual Conference on Neural Information Processing
Systems, vol. 37, Neural Information Processing Systems Foundation, 2024.
short: D. Beaglehole, P. Súkeník, M. Mondelli, M. Belkin, in:, 38th Annual Conference
on Neural Information Processing Systems, Neural Information Processing Systems
Foundation, 2024.
conference:
end_date: 2024-12-16
location: Vancouver, Canada
name: 'NeurIPS: Neural Information Processing Systems'
start_date: 2024-12-16
corr_author: '1'
date_created: 2025-01-27T11:11:40Z
date_published: 2024-12-01T00:00:00Z
date_updated: 2025-05-14T11:29:45Z
day: '01'
department:
- _id: GradSch
- _id: MaMo
external_id:
arxiv:
- '2402.13728'
intvolume: ' 37'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://openreview.net/forum?id=lJ1jdl2K9k
month: '12'
oa: 1
oa_version: Preprint
project:
- _id: 059876FA-7A3F-11EA-A408-12923DDC885E
name: Prix Lopez-Loretta 2019 - Marco Mondelli
publication: 38th Annual Conference on Neural Information Processing Systems
publication_identifier:
eissn:
- 1049-5258
publication_status: published
publisher: Neural Information Processing Systems Foundation
quality_controlled: '1'
scopus_import: '1'
status: public
title: Average gradient outer product as a mechanism for deep neural collapse
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 37
year: '2024'
...
---
OA_place: publisher
OA_type: gold
_id: '18891'
abstract:
- lang: eng
text: "Deep neural networks (DNNs) exhibit a surprising structure in their final
layer\r\nknown as neural collapse (NC), and a growing body of works has currently
investigated the propagation of neural collapse to earlier layers of DNNs – a
phenomenon\r\ncalled deep neural collapse (DNC). However, existing theoretical
results are restricted to special cases: linear models, only two layers or binary
classification.\r\nIn contrast, we focus on non-linear models of arbitrary depth
in multi-class classification and reveal a surprising qualitative shift. As soon
as we go beyond two\r\nlayers or two classes, DNC stops being optimal for the
deep unconstrained features\r\nmodel (DUFM) – the standard theoretical framework
for the analysis of collapse.\r\nThe main culprit is a low-rank bias of multi-layer
regularization schemes: this bias\r\nleads to optimal solutions of even lower
rank than the neural collapse. We support\r\nour theoretical findings with experiments
on both DUFM and real data, which show\r\nthe emergence of the low-rank structure
in the solution found by gradient descent."
acknowledged_ssus:
- _id: ScienComp
acknowledgement: Marco Mondelli is partially supported by the 2019 Lopez-Loreta prize.
This research was supported by the Scientific Service Units (SSU) of ISTA through
resources provided by Scientific Computing (SciComp).
alternative_title:
- Advances in Neural Information Processing Systems
article_processing_charge: No
arxiv: 1
author:
- first_name: Peter
full_name: Súkeník, Peter
id: d64d6a8d-eb8e-11eb-b029-96fd216dec3c
last_name: Súkeník
- first_name: Christoph
full_name: Lampert, Christoph
id: 40C20FD2-F248-11E8-B48F-1D18A9856A87
last_name: Lampert
orcid: 0000-0001-8622-7887
- first_name: Marco
full_name: Mondelli, Marco
id: 27EB676C-8706-11E9-9510-7717E6697425
last_name: Mondelli
orcid: 0000-0002-3242-7020
citation:
ama: 'Súkeník P, Lampert C, Mondelli M. Neural collapse versus low-rank bias: Is
deep neural collapse really optimal? In: 38th Annual Conference on Neural Information
Processing Systems. Vol 37. Neural Information Processing Systems Foundation;
2024.'
apa: 'Súkeník, P., Lampert, C., & Mondelli, M. (2024). Neural collapse versus
low-rank bias: Is deep neural collapse really optimal? In 38th Annual Conference
on Neural Information Processing Systems (Vol. 37). Vancouver, Canada: Neural
Information Processing Systems Foundation.'
chicago: 'Súkeník, Peter, Christoph Lampert, and Marco Mondelli. “Neural Collapse
versus Low-Rank Bias: Is Deep Neural Collapse Really Optimal?” In 38th Annual
Conference on Neural Information Processing Systems, Vol. 37. Neural Information
Processing Systems Foundation, 2024.'
ieee: 'P. Súkeník, C. Lampert, and M. Mondelli, “Neural collapse versus low-rank
bias: Is deep neural collapse really optimal?,” in 38th Annual Conference on
Neural Information Processing Systems, Vancouver, Canada, 2024, vol. 37.'
ista: 'Súkeník P, Lampert C, Mondelli M. 2024. Neural collapse versus low-rank bias:
Is deep neural collapse really optimal? 38th Annual Conference on Neural Information
Processing Systems. NeurIPS: Neural Information Processing Systems, Advances in
Neural Information Processing Systems, vol. 37.'
mla: 'Súkeník, Peter, et al. “Neural Collapse versus Low-Rank Bias: Is Deep Neural
Collapse Really Optimal?” 38th Annual Conference on Neural Information Processing
Systems, vol. 37, Neural Information Processing Systems Foundation, 2024.'
short: P. Súkeník, C. Lampert, M. Mondelli, in:, 38th Annual Conference on Neural
Information Processing Systems, Neural Information Processing Systems Foundation,
2024.
conference:
end_date: 2024-12-16
location: Vancouver, Canada
name: 'NeurIPS: Neural Information Processing Systems'
start_date: 2024-12-16
corr_author: '1'
date_created: 2025-01-27T11:15:18Z
date_published: 2024-12-01T00:00:00Z
date_updated: 2025-06-04T07:19:21Z
day: '01'
ddc:
- '000'
department:
- _id: GradSch
- _id: MaMo
- _id: ChLa
external_id:
arxiv:
- '2405.14468'
file:
- access_level: open_access
checksum: b7b79f1ea3ac1e9e11b3d91faaeb0780
content_type: application/pdf
creator: dernst
date_created: 2025-02-04T08:11:25Z
date_updated: 2025-02-04T08:11:25Z
file_id: '18989'
file_name: 2024_NeurIPS_Sukenik.pdf
file_size: 1784118
relation: main_file
success: 1
file_date_updated: 2025-02-04T08:11:25Z
has_accepted_license: '1'
intvolume: ' 37'
language:
- iso: eng
month: '12'
oa: 1
oa_version: Published Version
project:
- _id: 059876FA-7A3F-11EA-A408-12923DDC885E
name: Prix Lopez-Loretta 2019 - Marco Mondelli
publication: 38th Annual Conference on Neural Information Processing Systems
publication_status: published
publisher: Neural Information Processing Systems Foundation
quality_controlled: '1'
status: public
title: 'Neural collapse versus low-rank bias: Is deep neural collapse really optimal?'
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: 37
year: '2024'
...
---
OA_place: repository
OA_type: gold
_id: '18895'
abstract:
- lang: eng
text: 'ISTAnt is a new ecological dataset for social immunity and represents the
first real-world benchmark for causal inference downstream tasks on high-dimensional
observations. It analyzes grooming behavior in the ant Lasius neglectus in groups
of three worker ants. The workers for the experiment were obtained from their
laboratory stock colony, which had been collected from the field in 2022 in the
Botanical Garden Jena, Germany. Ant collection and all experimental work were
performed in compliance with international, national and institutional regulations
and ethical guidelines. For the experiment, the body surface of one of the three
ants was treated with a suspension of either of two microparticle types (diameter
~5 µm) to induce grooming by the two nestmates, which were individually color-coded
by application of a dot of blue or orange paint, respectively. The three ants
were housed in small plastic containers (diameter 28mm, height 30mm) with moistened,
plastered ground and the interior walls covered with PTFE (polytetrafluoroethane)
to hamper climbing by the ants. Filming occurred in a temperature- and humidity-controlled
room at 23°C within a custom-made filming box with controlled lighting and ventilation
conditions. We set up nine ant groups at a time (always containing both treatments)
and placed them randomly on positions 1-9 marked on the floor in a 3x3 grid, about
3mm from each other. The experiment was performed on two consecutive days. Videos
were acquired using a USB camera (FLIR blackfly S BFS-U3-120S4C, Teledyne FLIR)
with a high-performance lens (HP Series 25mm Focal Length, Edmund optics 86-572)
in OBS studio 29.0.0 \citep{bailey2017obs} at a framerate of 30 FPS and a resolution
of 2500x2500 pixels. From each original video (105x105 mm), we generated nine
individual videos .mkv (each ~32x32 mm, 770x770 pixels) by determining exact coordinates
per container from one frame in GIMP 2.10.36 and cropping of the videos with FFmpeg
6.1.1. Annotation was performed over two consecutive days by three observers who
had not been involved in the experimental setup or recording and were unaware
of the treatment assignments to ensure bias-free behavioral annotation. They annotated
the behavior of the ants during video observations, using custom-made software
that saves the start and end frames of behaviors marked in a .csv file (see ''annotations''
folder). In one of the videos, one of the nestmates'' legs got inadvertently stuck
to its body surface during the color-coding, interfering with its behavior, so
the video was discarded. This left 44 videos from 5 independent setups (n=24 of
treatment 1 and n=20 of treatment 2) of 10 minutes each for a total of 792 000
annotated frames (see ''video'' folder). For each video, we provide the following
information: the number of the set to which it belongs (1-5); the number of the
position within the set reflecting the position of the ant group under the camera
(1-9), for which we also provide ‘coordinates’ in the 3x3 grid (taking values
-1/0/1 for both X and Y axis); treatment (1 or 2); the hour of the day when the
recording was started (in 24h CEST); experimental day (A or B); the top left coordinate
of the cropping square from the original video (CropX/CropY); the person annotating
the video (given as A, B, C); the date of annotation (1: first day, 2: second
day) and in which order the videos were annotated by each person, both reflecting
a possible training effect of the person (see ''experiments_settings.csv'' file).'
article_processing_charge: No
author:
- first_name: Riccardo
full_name: Cadei, Riccardo
id: 0fa8b76f-72f0-11ef-b75a-a5da96e5ad6b
last_name: Cadei
- first_name: Francesco
full_name: Locatello, Francesco
id: 26cfd52f-2483-11ee-8040-88983bcc06d4
last_name: Locatello
orcid: 0000-0002-4850-0683
- first_name: Sylvia M
full_name: Cremer, Sylvia M
id: 2F64EC8C-F248-11E8-B48F-1D18A9856A87
last_name: Cremer
orcid: 0000-0002-2193-3868
- first_name: Lukas
full_name: Lindorfer, Lukas
id: 85f0e6d3-06b3-11ec-8982-8c5049fa4455
last_name: Lindorfer
- first_name: Cordelia
full_name: Schmid, Cordelia
last_name: Schmid
citation:
ama: Cadei R, Locatello F, Cremer S, Lindorfer L, Schmid C. ISTAnt. 2024. doi:10.6084/M9.FIGSHARE.26484934.V2
apa: Cadei, R., Locatello, F., Cremer, S., Lindorfer, L., & Schmid, C. (2024).
ISTAnt. Institute of Science and Technology Austria. https://doi.org/10.6084/M9.FIGSHARE.26484934.V2
chicago: Cadei, Riccardo, Francesco Locatello, Sylvia Cremer, Lukas Lindorfer, and
Cordelia Schmid. “ISTAnt.” Institute of Science and Technology Austria, 2024.
https://doi.org/10.6084/M9.FIGSHARE.26484934.V2.
ieee: R. Cadei, F. Locatello, S. Cremer, L. Lindorfer, and C. Schmid, “ISTAnt.”
Institute of Science and Technology Austria, 2024.
ista: Cadei R, Locatello F, Cremer S, Lindorfer L, Schmid C. 2024. ISTAnt, Institute
of Science and Technology Austria, 10.6084/M9.FIGSHARE.26484934.V2.
mla: Cadei, Riccardo, et al. ISTAnt. Institute of Science and Technology
Austria, 2024, doi:10.6084/M9.FIGSHARE.26484934.V2.
short: R. Cadei, F. Locatello, S. Cremer, L. Lindorfer, C. Schmid, (2024).
corr_author: '1'
date_created: 2025-01-27T11:45:43Z
date_published: 2024-10-23T00:00:00Z
date_updated: 2025-01-27T11:58:38Z
day: '23'
ddc:
- '570'
department:
- _id: SyCr
- _id: FrLo
- _id: GradSch
doi: 10.6084/M9.FIGSHARE.26484934.V2
main_file_link:
- open_access: '1'
url: https://10.6084/M9.FIGSHARE.26484934.V2
month: '10'
oa: 1
oa_version: Published Version
publisher: Institute of Science and Technology Austria
related_material:
record:
- id: '18847'
relation: used_in_publication
status: public
status: public
title: ISTAnt
type: research_data_reference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2024'
...
---
OA_place: publisher
OA_type: gold
_id: '18897'
abstract:
- lang: eng
text: 'Score-based generative models (SGMs) are powerful tools to sample from complex
data distributions. Their underlying idea is to (i) run a forward process for
time T1 by adding noise to the data, (ii) estimate its score function, and (iii)
use such estimate to run a reverse process. As the reverse process is initialized
with the stationary distribution of the forward one, the existing analysis paradigm
requires T1→∞. This is however problematic: from a theoretical viewpoint, for
a given precision of the score approximation, the convergence guarantee fails
as T1 diverges; from a practical viewpoint, a large T1 increases computational
costs and leads to error propagation. This paper addresses the issue by considering
a version of the popular predictor-corrector scheme: after running the forward
process, we first estimate the final distribution via an inexact Langevin dynamics
and then revert the process. Our key technical contribution is to provide convergence
guarantees which require to run the forward process only for a fixed finite time
T1. Our bounds exhibit a mild logarithmic dependence on the input dimension and
the subgaussian norm of the target distribution, have minimal assumptions on the
data, and require only to control the L2 loss on the score approximation, which
is the quantity minimized in practice.'
acknowledgement: "Francesco Pedrotti and Jan Maas acknowledge support by the Austrian
Science Fund (FWF) project 10.55776/F65. Marco Mondelli acknowledges support by
the 2019 Lopez-Loreta prize.\r\n"
alternative_title:
- TMLR
article_processing_charge: No
arxiv: 1
author:
- first_name: Francesco
full_name: Pedrotti, Francesco
id: d3ac8ac6-dc8d-11ea-abe3-e2a9628c4c3c
last_name: Pedrotti
- first_name: Jan
full_name: Maas, Jan
id: 4C5696CE-F248-11E8-B48F-1D18A9856A87
last_name: Maas
orcid: 0000-0002-0845-1338
- first_name: Marco
full_name: Mondelli, Marco
id: 27EB676C-8706-11E9-9510-7717E6697425
last_name: Mondelli
orcid: 0000-0002-3242-7020
citation:
ama: 'Pedrotti F, Maas J, Mondelli M. Improved convergence of score-based diffusion
models via prediction-correction. In: Transactions on Machine Learning Research.
; 2024.'
apa: Pedrotti, F., Maas, J., & Mondelli, M. (2024). Improved convergence of
score-based diffusion models via prediction-correction. In Transactions on
Machine Learning Research.
chicago: Pedrotti, Francesco, Jan Maas, and Marco Mondelli. “Improved Convergence
of Score-Based Diffusion Models via Prediction-Correction.” In Transactions
on Machine Learning Research, 2024.
ieee: F. Pedrotti, J. Maas, and M. Mondelli, “Improved convergence of score-based
diffusion models via prediction-correction,” in Transactions on Machine Learning
Research, 2024.
ista: Pedrotti F, Maas J, Mondelli M. 2024. Improved convergence of score-based
diffusion models via prediction-correction. Transactions on Machine Learning Research.
, TMLR, .
mla: Pedrotti, Francesco, et al. “Improved Convergence of Score-Based Diffusion
Models via Prediction-Correction.” Transactions on Machine Learning Research,
2024.
short: F. Pedrotti, J. Maas, M. Mondelli, in:, Transactions on Machine Learning
Research, 2024.
corr_author: '1'
date_created: 2025-01-27T12:18:05Z
date_published: 2024-06-01T00:00:00Z
date_updated: 2025-04-15T08:31:35Z
day: '01'
ddc:
- '000'
department:
- _id: JaMa
- _id: MaMo
external_id:
arxiv:
- '2305.14164'
file:
- access_level: open_access
checksum: 76a1fd5afd8ee6f7ae0e5912d7dbf6b4
content_type: application/pdf
creator: dernst
date_created: 2025-01-27T12:19:44Z
date_updated: 2025-01-27T12:19:44Z
file_id: '18898'
file_name: 2024_TMLR_Pedrotti.pdf
file_size: 780315
relation: main_file
success: 1
file_date_updated: 2025-01-27T12:19:44Z
has_accepted_license: '1'
language:
- iso: eng
month: '06'
oa: 1
oa_version: Published Version
project:
- _id: fc31cba2-9c52-11eb-aca3-ff467d239cd2
grant_number: F6504
name: Taming Complexity in Partial Differential Systems
- _id: 059876FA-7A3F-11EA-A408-12923DDC885E
name: Prix Lopez-Loretta 2019 - Marco Mondelli
publication: Transactions on Machine Learning Research
publication_identifier:
issn:
- 2835-8856
publication_status: published
quality_controlled: '1'
related_material:
record:
- id: '17350'
relation: earlier_version
status: public
scopus_import: '1'
status: public
title: Improved convergence of score-based diffusion models via prediction-correction
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: '2024'
...
---
_id: '18899'
abstract:
- lang: eng
text: "The flourishing theory of classical optimal transport concerns mass transportation
at minimal cost. This book introduces the reader to optimal transport on quantum
structures, i.e., optimal transportation between quantum states and related non-commutative
concepts of mass transportation. It contains lecture notes on\r\n\r\nclassical
optimal transport and Wasserstein gradient flows\r\ndynamics and quantum optimal
transport\r\nquantum couplings and many-body problems\r\nquantum channels and
qubits\r\n\r\nThese notes are based on lectures given by the authors at the \"Optimal
Transport on Quantum Structures\" School held at the Erdös Center in Budapest
in the fall of 2022. The lecture notes are complemented by two survey chapters
presenting the state of the art in different research areas of non-commutative
optimal transport."
alternative_title:
- Bolyai Society Mathematical Studies
article_processing_charge: No
citation:
ama: 'Maas J, Rademacher SAE, Titkos T, Virosztek D, eds. Optimal Transport on
Quantum Structures. Vol 29. Cham: Springer Nature; 2024. doi:10.1007/978-3-031-50466-2'
apa: 'Maas, J., Rademacher, S. A. E., Titkos, T., & Virosztek, D. (Eds.). (2024).
Optimal Transport on Quantum Structures (Vol. 29). Cham: Springer Nature.
https://doi.org/10.1007/978-3-031-50466-2'
chicago: 'Maas, Jan, Simone Anna Elvira Rademacher, Tamás Titkos, and Daniel Virosztek,
eds. Optimal Transport on Quantum Structures. Vol. 29. BSMS. Cham: Springer
Nature, 2024. https://doi.org/10.1007/978-3-031-50466-2.'
ieee: 'J. Maas, S. A. E. Rademacher, T. Titkos, and D. Virosztek, Eds., Optimal
Transport on Quantum Structures, vol. 29. Cham: Springer Nature, 2024.'
ista: 'Maas J, Rademacher SAE, Titkos T, Virosztek D eds. 2024. Optimal Transport
on Quantum Structures, Cham: Springer Nature,p.'
mla: Maas, Jan, et al., editors. Optimal Transport on Quantum Structures.
Vol. 29, Springer Nature, 2024, doi:10.1007/978-3-031-50466-2.
short: J. Maas, S.A.E. Rademacher, T. Titkos, D. Virosztek, eds., Optimal Transport
on Quantum Structures, Springer Nature, Cham, 2024.
date_created: 2025-01-27T12:26:03Z
date_published: 2024-09-19T00:00:00Z
date_updated: 2025-02-17T12:22:18Z
day: '19'
department:
- _id: JaMa
doi: 10.1007/978-3-031-50466-2
editor:
- first_name: Jan
full_name: Maas, Jan
id: 4C5696CE-F248-11E8-B48F-1D18A9856A87
last_name: Maas
orcid: 0000-0002-0845-1338
- first_name: Simone Anna Elvira
full_name: Rademacher, Simone Anna Elvira
id: 856966FE-A408-11E9-977E-802DE6697425
last_name: Rademacher
orcid: 0000-0001-5059-4466
- first_name: Tamás
full_name: Titkos, Tamás
last_name: Titkos
- first_name: Daniel
full_name: Virosztek, Daniel
id: 48DB45DA-F248-11E8-B48F-1D18A9856A87
last_name: Virosztek
orcid: 0000-0003-1109-5511
intvolume: ' 29'
language:
- iso: eng
month: '09'
oa_version: None
place: Cham
publication_identifier:
eisbn:
- '9783031504662'
eissn:
- 2947-9460
isbn:
- '9783031504655'
issn:
- 1217-4696
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
series_title: BSMS
status: public
title: Optimal Transport on Quantum Structures
type: book_editor
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 29
year: '2024'
...
---
OA_place: publisher
OA_type: hybrid
_id: '18900'
abstract:
- lang: eng
text: We prove that certain closable derivations on the GNS Hilbert space associated
with a non-tracial weight on a von Neumann algebra give rise to GNS-symmetric
semigroups of contractive completely positive maps on the von Neumann algebra.
acknowledgement: 'The author was funded by the Austrian Science Fund under the Esprit
Programme [ESP 156]. For the purpose of Open Access, the authors have applied a
CC BY public copyright licence to any Author Accepted Manuscript version arising
from this submission. '
article_processing_charge: Yes (via OA deal)
article_type: original
author:
- first_name: Melchior
full_name: Wirth, Melchior
id: 88644358-0A0E-11EA-8FA5-49A33DDC885E
last_name: Wirth
orcid: 0000-0002-0519-4241
citation:
ama: Wirth M. Modular completely Dirichlet forms as squares of derivations. International
Mathematics Research Notices. 2024;2024(14):10597-10614. doi:10.1093/imrn/rnae092
apa: Wirth, M. (2024). Modular completely Dirichlet forms as squares of derivations.
International Mathematics Research Notices. Oxford University Press. https://doi.org/10.1093/imrn/rnae092
chicago: Wirth, Melchior. “Modular Completely Dirichlet Forms as Squares of Derivations.”
International Mathematics Research Notices. Oxford University Press, 2024.
https://doi.org/10.1093/imrn/rnae092.
ieee: M. Wirth, “Modular completely Dirichlet forms as squares of derivations,”
International Mathematics Research Notices, vol. 2024, no. 14. Oxford University
Press, pp. 10597–10614, 2024.
ista: Wirth M. 2024. Modular completely Dirichlet forms as squares of derivations.
International Mathematics Research Notices. 2024(14), 10597–10614.
mla: Wirth, Melchior. “Modular Completely Dirichlet Forms as Squares of Derivations.”
International Mathematics Research Notices, vol. 2024, no. 14, Oxford University
Press, 2024, pp. 10597–614, doi:10.1093/imrn/rnae092.
short: M. Wirth, International Mathematics Research Notices 2024 (2024) 10597–10614.
corr_author: '1'
date_created: 2025-01-27T12:36:10Z
date_published: 2024-07-01T00:00:00Z
date_updated: 2025-09-09T12:02:46Z
day: '01'
ddc:
- '510'
department:
- _id: JaMa
doi: 10.1093/imrn/rnae092
external_id:
isi:
- '001222279400001'
file:
- access_level: open_access
checksum: 3e1f80d58ada0c60a58f35df8080967e
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creator: dernst
date_created: 2025-01-27T12:38:10Z
date_updated: 2025-01-27T12:38:10Z
file_id: '18901'
file_name: 2024_IMRN_Wirth.pdf
file_size: 689984
relation: main_file
success: 1
file_date_updated: 2025-01-27T12:38:10Z
has_accepted_license: '1'
intvolume: ' 2024'
isi: 1
issue: '14'
language:
- iso: eng
month: '07'
oa: 1
oa_version: Published Version
page: 10597-10614
project:
- _id: 34c6ea2d-11ca-11ed-8bc3-c04f3c502833
grant_number: ESP156_N
name: Gradient flow techniques for quantum Markov semigroups
publication: International Mathematics Research Notices
publication_identifier:
eissn:
- 1687-0247
issn:
- 1073-7928
publication_status: published
publisher: Oxford University Press
quality_controlled: '1'
scopus_import: '1'
status: public
title: Modular completely Dirichlet forms as squares of derivations
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: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 2024
year: '2024'
...