---
OA_place: repository
OA_type: green
_id: '21257'
abstract:
- lang: eng
text: 'We investigate the problem of accurate sparse fine-tuning of large language
models (LLMs), that is, fine-tuning pre-trained LLMs on specialized tasks, while
inducing sparsity in their weights. Our work is motivated by experiments showing
that standard loss-based fine-tuning methods are not able to achieve high accuracy
in this setting, especially at high sparsity targets. To address this issue, we
perform a detailed study of knowledge distillation losses for fine-tuning of sparse
models. We determine an L2-based distillation approach that we term ‘SquareHead’,
which enables accurate recovery even at higher sparsities. Investigating the question
of efficient inference, we show that sparse LLMs can be executed faster by taking
advantage of sparsity. Specifically, we exhibit end-to-end results showing speedups
enabled by sparsity, while recovering accuracy, on the following models and tasks,
respectively: T5 for language translation, Whisper for speech translation, and
open GPT-type models such as the Mosaic Pre-Trained Transformer (MPT) and Llama-2
models for text generation. In particular, for popular generative tasks, we show
for the first time that sparse fine-tuning can reach 75% sparsity without drops
in accuracy, and provide notable end-to-end speedups for inference on CPUs. Moreover,
we also highlight that sparsity is compatible with other compression approaches,
such as quantization.'
acknowledgement: We would like to thank Eugenia Iofinova for useful comments on an
earlier version of this draft, and Artur Niederfahrenhorst for useful suggestions
regarding fine-tuning on the GSM8k dataset.
alternative_title:
- 'Machine Translation: Technologies and Applications'
article_processing_charge: No
arxiv: 1
author:
- first_name: Eldar
full_name: Kurtic, Eldar
id: 47beb3a5-07b5-11eb-9b87-b108ec578218
last_name: Kurtic
- first_name: Denis
full_name: Kuznedelev, Denis
last_name: Kuznedelev
- first_name: Elias
full_name: Frantar, Elias
id: 09a8f98d-ec99-11ea-ae11-c063a7b7fe5f
last_name: Frantar
- first_name: Michael
full_name: Goinv, Michael
last_name: Goinv
- first_name: Shubhra
full_name: Pandit, Shubhra
last_name: Pandit
- first_name: Abhinav
full_name: Agarwalla, Abhinav
last_name: Agarwalla
- first_name: Tuan
full_name: Nguyen, Tuan
last_name: Nguyen
- first_name: Alexandre
full_name: Marques, Alexandre
last_name: Marques
- first_name: Mark
full_name: Kurtz, Mark
last_name: Kurtz
- first_name: Dan-Adrian
full_name: Alistarh, Dan-Adrian
id: 4A899BFC-F248-11E8-B48F-1D18A9856A87
last_name: Alistarh
orcid: 0000-0003-3650-940X
citation:
ama: 'Kurtic E, Kuznedelev D, Frantar E, et al. Sparse Fine-Tuning for Inference
Acceleration of Large Language Models. In: Passban P, Way A, Rezagholizadeh M,
eds. Enhancing LLM Performance. Efficacy, Fine-Tuning, and Inference Techniques.
Springer Nature; 2025:83-97. doi:10.1007/978-3-031-85747-8_6'
apa: Kurtic, E., Kuznedelev, D., Frantar, E., Goinv, M., Pandit, S., Agarwalla,
A., … Alistarh, D.-A. (2025). Sparse Fine-Tuning for Inference Acceleration of
Large Language Models. In P. Passban, A. Way, & M. Rezagholizadeh (Eds.),
Enhancing LLM Performance. Efficacy, Fine-Tuning, and Inference Techniques
(pp. 83–97). Springer Nature. https://doi.org/10.1007/978-3-031-85747-8_6
chicago: Kurtic, Eldar, Denis Kuznedelev, Elias Frantar, Michael Goinv, Shubhra
Pandit, Abhinav Agarwalla, Tuan Nguyen, Alexandre Marques, Mark Kurtz, and Dan-Adrian
Alistarh. “Sparse Fine-Tuning for Inference Acceleration of Large Language Models.”
In Enhancing LLM Performance. Efficacy, Fine-Tuning, and Inference Techniques,
edited by Peyman Passban, Andy Way, and Mehdi Rezagholizadeh, 83–97. Springer
Nature, 2025. https://doi.org/10.1007/978-3-031-85747-8_6.
ieee: E. Kurtic et al., “Sparse Fine-Tuning for Inference Acceleration of
Large Language Models,” in Enhancing LLM Performance. Efficacy, Fine-Tuning,
and Inference Techniques, P. Passban, A. Way, and M. Rezagholizadeh, Eds.
Springer Nature, 2025, pp. 83–97.
ista: 'Kurtic E, Kuznedelev D, Frantar E, Goinv M, Pandit S, Agarwalla A, Nguyen
T, Marques A, Kurtz M, Alistarh D-A. 2025.Sparse Fine-Tuning for Inference Acceleration
of Large Language Models. In: Enhancing LLM Performance. Efficacy, Fine-Tuning,
and Inference Techniques. Machine Translation: Technologies and Applications,
, 83–97.'
mla: Kurtic, Eldar, et al. “Sparse Fine-Tuning for Inference Acceleration of Large
Language Models.” Enhancing LLM Performance. Efficacy, Fine-Tuning, and Inference
Techniques, edited by Peyman Passban et al., Springer Nature, 2025, pp. 83–97,
doi:10.1007/978-3-031-85747-8_6.
short: E. Kurtic, D. Kuznedelev, E. Frantar, M. Goinv, S. Pandit, A. Agarwalla,
T. Nguyen, A. Marques, M. Kurtz, D.-A. Alistarh, in:, P. Passban, A. Way, M. Rezagholizadeh
(Eds.), Enhancing LLM Performance. Efficacy, Fine-Tuning, and Inference Techniques,
Springer Nature, 2025, pp. 83–97.
corr_author: '1'
date_created: 2026-02-16T15:57:53Z
date_published: 2025-07-05T00:00:00Z
date_updated: 2026-02-19T09:26:54Z
day: '05'
department:
- _id: DaAl
- _id: GradSch
doi: 10.1007/978-3-031-85747-8_6
editor:
- first_name: Peyman
full_name: Passban, Peyman
last_name: Passban
- first_name: Andy
full_name: Way, Andy
last_name: Way
- first_name: Mehdi
full_name: Rezagholizadeh, Mehdi
last_name: Rezagholizadeh
external_id:
arxiv:
- '2310.06927'
fulldoi: https://doi.org/10.1007/978-3-031-85747-8_6
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2310.06927
month: '07'
oa: 1
oa_version: Preprint
page: 83-97
publication: Enhancing LLM Performance. Efficacy, Fine-Tuning, and Inference Techniques
publication_identifier:
eisbn:
- '9783031857478'
eissn:
- 2522-803X
isbn:
- '9783031857461'
issn:
- 2522-8021
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
status: public
title: Sparse Fine-Tuning for Inference Acceleration of Large Language Models
type: book_chapter
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2025'
...
---
DOAJ_listed: '1'
OA_place: publisher
OA_type: gold
PlanS_conform: '1'
_id: '21269'
abstract:
- lang: eng
text: The spatial organization of chromatin within the nucleus plays a crucial role
in gene expression and genome function. However, the quantitative relationship
between this organization and nuclear biochemical processes remains under debate.
In this study, we present a graph-based generative model, bioSBM, designed to
capture long-range chromatin interaction patterns from Hi-C data and, importantly,
simultaneously link these patterns to biochemical features. Applying bioSBM to
Hi-C maps of the GM12878 lymphoblastoid cell line, we identified a latent structure
of chromatin interactions, revealing seven distinct communities that strongly
align with known biological annotations. Additionally, we infer a linear transformation
that maps biochemical observables, such as histone marks, to the parameters of
the generative graph model, enabling accurate genome-wide predictions of chromatin
contact maps on out-of-sample data, both within the same cell line and on the
completely unseen HCT116 cell line under RAD21 depletion. These findings highlight
bioSBM's potential as a powerful tool for elucidating the relationship between
biochemistry and chromatin architecture and predicting long-range genome organization
from independent biochemical data.
acknowledgement: G.S. acknowledges co-funding from Next Generation EU, in the context
of the National Recovery and Resilience Plan, Investment PE1 - Project FAIR “Future
Artificial Intelligence Research”. This resource was co-financed by the Next Generation
EU [DM 1555 del 11.10.22]. A.R. acknowledges financial support from PNRR Grant CN
00000013 CN-HPC, M4C2I1.4, spoke 7, funded by Next Generation EU.
article_number: '043006'
article_processing_charge: Yes
article_type: original
arxiv: 1
author:
- first_name: Chen Y
full_name: Zhang, Chen Y
id: 81b43fb8-c9d5-11ef-bf68-ade532a1f204
last_name: Zhang
- first_name: Angelo
full_name: Rosa, Angelo
last_name: Rosa
- first_name: Guido
full_name: Sanguinetti, Guido
last_name: Sanguinetti
citation:
ama: 'Zhang CY, Rosa A, Sanguinetti G. bioSBM: A random graph model to integrate
epigenomic data in chromatin structure prediction. PRX Life. 2025;3(4).
doi:10.1103/gy1p-4256'
apa: 'Zhang, C. Y., Rosa, A., & Sanguinetti, G. (2025). bioSBM: A random graph
model to integrate epigenomic data in chromatin structure prediction. PRX Life.
American Physical Society. https://doi.org/10.1103/gy1p-4256'
chicago: 'Zhang, Chen Y, Angelo Rosa, and Guido Sanguinetti. “BioSBM: A Random Graph
Model to Integrate Epigenomic Data in Chromatin Structure Prediction.” PRX
Life. American Physical Society, 2025. https://doi.org/10.1103/gy1p-4256.'
ieee: 'C. Y. Zhang, A. Rosa, and G. Sanguinetti, “bioSBM: A random graph model to
integrate epigenomic data in chromatin structure prediction,” PRX Life,
vol. 3, no. 4. American Physical Society, 2025.'
ista: 'Zhang CY, Rosa A, Sanguinetti G. 2025. bioSBM: A random graph model to integrate
epigenomic data in chromatin structure prediction. PRX Life. 3(4), 043006.'
mla: 'Zhang, Chen Y., et al. “BioSBM: A Random Graph Model to Integrate Epigenomic
Data in Chromatin Structure Prediction.” PRX Life, vol. 3, no. 4, 043006,
American Physical Society, 2025, doi:10.1103/gy1p-4256.'
short: C.Y. Zhang, A. Rosa, G. Sanguinetti, PRX Life 3 (2025).
corr_author: '1'
date_created: 2026-02-17T07:53:01Z
date_published: 2025-10-21T00:00:00Z
date_updated: 2026-02-18T08:01:00Z
day: '21'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.1103/gy1p-4256
external_id:
arxiv:
- '2409.14425'
file:
- access_level: open_access
checksum: 76ddfee3efdb4c9d085059b5a142ed78
content_type: application/pdf
creator: dernst
date_created: 2026-02-18T07:57:39Z
date_updated: 2026-02-18T07:57:39Z
file_id: '21314'
file_name: 2025_PRXLife_Zhang.pdf
file_size: 1888053
relation: main_file
success: 1
file_date_updated: 2026-02-18T07:57:39Z
fulldoi: https://doi.org/10.1103/gy1p-4256
has_accepted_license: '1'
intvolume: ' 3'
issue: '4'
language:
- iso: eng
license: https://creativecommons.org/licenses/by/4.0/
month: '10'
oa: 1
oa_version: Published Version
publication: PRX Life
publication_identifier:
issn:
- 2835-8279
publication_status: published
publisher: American Physical Society
quality_controlled: '1'
status: public
title: 'bioSBM: A random graph model to integrate epigenomic data in chromatin structure
prediction'
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: 3
year: '2025'
...
---
OA_place: repository
OA_type: green
_id: '21270'
abstract:
- lang: eng
text: "The one-dimensional Fröhlich model describing the motion of a single electron
interacting with optical phonons is a paradigmatic model of quantum many-body
physics. We predict the existence of an arbitrarily large number of bound excited
states in the strong-coupling limit and calculate their excitation energies. Numerical
simulations of a discretized model demonstrate the complete amelioration of the
projector Monte Carlo sign problem by walker annihilation in an infinite Hilbert
space. They reveal the threshold for the occurrence of the first bound excited
states at a value of \U0001D6FC≈1.73 for the dimensionless coupling constant.
This puts the threshold into the regime of intermediate interaction strength.
We find a significant spectral weight and increased phonon number of the bound
excited state at threshold."
acknowledgement: We are grateful to Dmytro Kolisnyk for his help in working out the
spectrum of the Hessian. This work was supported by the Marsden Fund of New Zealand
(Contract No. MAU2007) from government funding administered by the Royal Society
Te Apārangi and by a summer scholarship from Te Whai Ao – Dodd-Walls Centre for
Photonic and Quantum Technologies and the Physics Department, University of Auckland.
We acknowledge support by the New Zealand eScience Infrastructure (NeSI) high-performance
computing facilities in the form of a merit project allocation.
article_number: '184312'
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: J.
full_name: Taylor, J.
last_name: Taylor
- first_name: M.
full_name: Čufar, M.
last_name: Čufar
- first_name: David Johannes
full_name: Mitrouskas, David Johannes
id: cbddacee-2b11-11eb-a02e-a2e14d04e52d
last_name: Mitrouskas
- first_name: Robert
full_name: Seiringer, Robert
id: 4AFD0470-F248-11E8-B48F-1D18A9856A87
last_name: Seiringer
orcid: 0000-0002-6781-0521
- first_name: E.
full_name: Pahl, E.
last_name: Pahl
- first_name: J.
full_name: Brand, J.
last_name: Brand
citation:
ama: Taylor J, Čufar M, Mitrouskas DJ, Seiringer R, Pahl E, Brand J. Bound excited
states of Fröhlich polarons in one dimension. Physical Review B. 2025;112(18).
doi:10.1103/s9p9-jflq
apa: Taylor, J., Čufar, M., Mitrouskas, D. J., Seiringer, R., Pahl, E., & Brand,
J. (2025). Bound excited states of Fröhlich polarons in one dimension. Physical
Review B. American Physical Society. https://doi.org/10.1103/s9p9-jflq
chicago: Taylor, J., M. Čufar, David Johannes Mitrouskas, Robert Seiringer, E. Pahl,
and J. Brand. “Bound Excited States of Fröhlich Polarons in One Dimension.” Physical
Review B. American Physical Society, 2025. https://doi.org/10.1103/s9p9-jflq.
ieee: J. Taylor, M. Čufar, D. J. Mitrouskas, R. Seiringer, E. Pahl, and J. Brand,
“Bound excited states of Fröhlich polarons in one dimension,” Physical Review
B, vol. 112, no. 18. American Physical Society, 2025.
ista: Taylor J, Čufar M, Mitrouskas DJ, Seiringer R, Pahl E, Brand J. 2025. Bound
excited states of Fröhlich polarons in one dimension. Physical Review B. 112(18),
184312.
mla: Taylor, J., et al. “Bound Excited States of Fröhlich Polarons in One Dimension.”
Physical Review B, vol. 112, no. 18, 184312, American Physical Society,
2025, doi:10.1103/s9p9-jflq.
short: J. Taylor, M. Čufar, D.J. Mitrouskas, R. Seiringer, E. Pahl, J. Brand, Physical
Review B 112 (2025).
date_created: 2026-02-17T07:56:20Z
date_published: 2025-11-18T00:00:00Z
date_updated: 2026-02-18T08:23:59Z
day: '18'
department:
- _id: RoSe
doi: 10.1103/s9p9-jflq
external_id:
arxiv:
- '2506.02440 '
fulldoi: https://doi.org/10.1103/s9p9-jflq
intvolume: ' 112'
issue: '18'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: 'https://doi.org/10.48550/arXiv.2506.02440 '
month: '11'
oa: 1
oa_version: Preprint
publication: Physical Review B
publication_identifier:
eissn:
- 2469-9969
issn:
- 2469-9950
publication_status: published
publisher: American Physical Society
quality_controlled: '1'
scopus_import: '1'
status: public
title: Bound excited states of Fröhlich polarons in one dimension
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 112
year: '2025'
...
---
OA_place: repository
OA_type: green
_id: '21271'
abstract:
- lang: eng
text: For general non-Hermitian large random matrices X and deterministic deformation
matrices A, we prove that the local eigenvalue statistics of A+X close to the
typical edge points of its spectrum are universal. Furthermore, we show that,
under natural assumptions, on A the spectrum of A+X does not have outliers at
a distance larger than the natural fluctuation scale of the eigenvalues. As a
consequence, the number of eigenvalues in each component of Spec(A+X) is deterministic.
acknowledgement: The authors would like to thank the anonymous referee for providing
helpful comments and suggestions. We also thank Joscha Henheik and Volodymyr Riabov
for pointing out a gap in an earlier version of the proof of equation (3.18). The
first, third, and fourth authors are supported by ERC Advanced Grant “RMTBeyond”
No. 101020331.
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Andrew J
full_name: Campbell, Andrew J
id: 582b06a9-1f1c-11ee-b076-82ffce00dde4
last_name: Campbell
- first_name: Giorgio
full_name: Cipolloni, Giorgio
id: 42198EFA-F248-11E8-B48F-1D18A9856A87
last_name: Cipolloni
orcid: 0000-0002-4901-7992
- first_name: László
full_name: Erdös, László
id: 4DBD5372-F248-11E8-B48F-1D18A9856A87
last_name: Erdös
orcid: 0000-0001-5366-9603
- first_name: Hong Chang
full_name: Ji, Hong Chang
id: dd216c0a-c1f9-11eb-beaf-e9ea9d2de76d
last_name: Ji
citation:
ama: Campbell AJ, Cipolloni G, Erdös L, Ji HC. On the spectral edge of non-Hermitian
random matrices. The Annals of Probability. 2025;53(6):2256-2308. doi:10.1214/25-aop1761
apa: Campbell, A. J., Cipolloni, G., Erdös, L., & Ji, H. C. (2025). On the spectral
edge of non-Hermitian random matrices. The Annals of Probability. Institute
of Mathematical Statistics. https://doi.org/10.1214/25-aop1761
chicago: Campbell, Andrew J, Giorgio Cipolloni, László Erdös, and Hong Chang Ji.
“On the Spectral Edge of Non-Hermitian Random Matrices.” The Annals of Probability.
Institute of Mathematical Statistics, 2025. https://doi.org/10.1214/25-aop1761.
ieee: A. J. Campbell, G. Cipolloni, L. Erdös, and H. C. Ji, “On the spectral edge
of non-Hermitian random matrices,” The Annals of Probability, vol. 53,
no. 6. Institute of Mathematical Statistics, pp. 2256–2308, 2025.
ista: Campbell AJ, Cipolloni G, Erdös L, Ji HC. 2025. On the spectral edge of non-Hermitian
random matrices. The Annals of Probability. 53(6), 2256–2308.
mla: Campbell, Andrew J., et al. “On the Spectral Edge of Non-Hermitian Random Matrices.”
The Annals of Probability, vol. 53, no. 6, Institute of Mathematical Statistics,
2025, pp. 2256–308, doi:10.1214/25-aop1761.
short: A.J. Campbell, G. Cipolloni, L. Erdös, H.C. Ji, The Annals of Probability
53 (2025) 2256–2308.
corr_author: '1'
date_created: 2026-02-17T07:58:20Z
date_published: 2025-11-01T00:00:00Z
date_updated: 2026-02-18T08:35:38Z
day: '01'
department:
- _id: LaEr
doi: 10.1214/25-aop1761
ec_funded: 1
external_id:
arxiv:
- '2404.17512'
fulldoi: https://doi.org/10.1214/25-aop1761
intvolume: ' 53'
issue: '6'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2404.17512
month: '11'
oa: 1
oa_version: Preprint
page: 2256-2308
project:
- _id: 62796744-2b32-11ec-9570-940b20777f1d
call_identifier: H2020
grant_number: '101020331'
name: Random matrices beyond Wigner-Dyson-Mehta
publication: The Annals of Probability
publication_identifier:
eissn:
- 2168-894X
issn:
- 0091-1798
publication_status: published
publisher: Institute of Mathematical Statistics
quality_controlled: '1'
status: public
title: On the spectral edge of non-Hermitian random matrices
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 53
year: '2025'
...
---
OA_place: repository
OA_type: green
_id: '21272'
abstract:
- lang: eng
text: Finding the ground state of Ising spin glasses is notoriously difficult due
to disorder and frustration. Often, this challenge is framed as a combinatorial
optimization problem, for which a common strategy employs simulated annealing,
a Monte Carlo (MC)-based algorithm that updates spins one at a time. Yet, these
localized updates can cause the system to become trapped in local minima. Cluster
algorithms (CAs) were developed to address this limitation and have demonstrated
considerable success in studying ferromagnetic systems; however, they tend to
encounter percolation issues when applied to generic spin glasses. In this work,
we introduce a novel CA designed to tackle these challenges by leveraging precomputed
two-point correlations, aiming solve combinatorial optimization problems in the
form of Max-Cut more efficiently. In our approach, clusters are formed probabilistically
based on these correlations. Various classical and quantum algorithms can be employed
to generate correlations that embody information about the energy landscape of
the problem. By utilizing this information, the algorithm aims to identify groups
of spins whose simultaneous flipping induces large transitions in configuration
space with high acceptance probability - even at low energy levels - thereby escaping
local minima more effectively. Notably, clusters generated using correlations
from the Quantum Approximate Optimization Algorithm exhibit high acceptance rates
at low temperatures. These acceptance rates often increase with circuit depth,
accelerating the algorithm and enabling more efficient exploration of the solution
space.
acknowledgement: "P.J.E was partially funded by the German BMWK project QCHALLenge
(Grant No. 01MQ22008B).\r\n"
article_processing_charge: No
arxiv: 1
author:
- first_name: Peter J.
full_name: Eder, Peter J.
last_name: Eder
- first_name: Aron
full_name: Kerschbaumer, Aron
id: ade85a9c-3200-11ee-973b-91c1eb240410
last_name: Kerschbaumer
orcid: 0009-0002-2370-8661
- first_name: Jernej Rudi
full_name: Finžgar, Jernej Rudi
last_name: Finžgar
- first_name: Raimel A
full_name: Medina Ramos, Raimel A
id: CE680B90-D85A-11E9-B684-C920E6697425
last_name: Medina Ramos
orcid: 0000-0002-5383-2869
- first_name: Martin J. A.
full_name: Schuetz, Martin J. A.
last_name: Schuetz
- first_name: Helmut G.
full_name: Katzgraber, Helmut G.
last_name: Katzgraber
- first_name: Sarah
full_name: Braun, Sarah
last_name: Braun
- first_name: Christian B.
full_name: Mendl, Christian B.
last_name: Mendl
citation:
ama: 'Eder PJ, Kerschbaumer A, Finžgar JR, et al. Quantum-guided cluster algorithms
for combinatorial optimization. In: 2025 IEEE International Conference on Quantum
Computing and Engineering. IEEE; 2025. doi:10.1109/qce65121.2025.00033'
apa: 'Eder, P. J., Kerschbaumer, A., Finžgar, J. R., Medina Ramos, R. A., Schuetz,
M. J. A., Katzgraber, H. G., … Mendl, C. B. (2025). Quantum-guided cluster algorithms
for combinatorial optimization. In 2025 IEEE International Conference on Quantum
Computing and Engineering. Albuquerque, NM, United States: IEEE. https://doi.org/10.1109/qce65121.2025.00033'
chicago: Eder, Peter J., Aron Kerschbaumer, Jernej Rudi Finžgar, Raimel A Medina
Ramos, Martin J. A. Schuetz, Helmut G. Katzgraber, Sarah Braun, and Christian
B. Mendl. “Quantum-Guided Cluster Algorithms for Combinatorial Optimization.”
In 2025 IEEE International Conference on Quantum Computing and Engineering.
IEEE, 2025. https://doi.org/10.1109/qce65121.2025.00033.
ieee: P. J. Eder et al., “Quantum-guided cluster algorithms for combinatorial
optimization,” in 2025 IEEE International Conference on Quantum Computing and
Engineering, Albuquerque, NM, United States, 2025.
ista: 'Eder PJ, Kerschbaumer A, Finžgar JR, Medina Ramos RA, Schuetz MJA, Katzgraber
HG, Braun S, Mendl CB. 2025. Quantum-guided cluster algorithms for combinatorial
optimization. 2025 IEEE International Conference on Quantum Computing and Engineering.
QCE: International Conference on Quantum Computing and Engineering.'
mla: Eder, Peter J., et al. “Quantum-Guided Cluster Algorithms for Combinatorial
Optimization.” 2025 IEEE International Conference on Quantum Computing and
Engineering, IEEE, 2025, doi:10.1109/qce65121.2025.00033.
short: P.J. Eder, A. Kerschbaumer, J.R. Finžgar, R.A. Medina Ramos, M.J.A. Schuetz,
H.G. Katzgraber, S. Braun, C.B. Mendl, in:, 2025 IEEE International Conference
on Quantum Computing and Engineering, IEEE, 2025.
conference:
end_date: 2025-09-05
location: Albuquerque, NM, United States
name: 'QCE: International Conference on Quantum Computing and Engineering'
start_date: 2025-08-30
corr_author: '1'
date_created: 2026-02-17T08:00:17Z
date_published: 2025-09-01T00:00:00Z
date_updated: 2026-02-18T08:45:56Z
day: '01'
department:
- _id: MaSe
doi: 10.1109/qce65121.2025.00033
external_id:
arxiv:
- '2508.10656'
fulldoi: https://doi.org/10.1109/qce65121.2025.00033
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2508.10656
month: '09'
oa: 1
oa_version: Preprint
publication: 2025 IEEE International Conference on Quantum Computing and Engineering
publication_identifier:
eisbn:
- '9798331557362'
publication_status: published
publisher: IEEE
quality_controlled: '1'
status: public
title: Quantum-guided cluster algorithms for combinatorial optimization
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2025'
...
---
OA_place: repository
OA_type: green
_id: '21309'
abstract:
- lang: eng
text: The polarization of light is a critically under-utilized, rich source of information
in astronomy. For stars in particular, surface magnetism polarization that can
be detected and measured with spectro-polarimetry. Many questions about these
surface fields remain unanswered due to a lack of dedicated instruments capable
of probing weak and strong surface magnetic fields for the entire mass range of
stars, from M-dwarfs (and even substellar objects) to massive O-type stars at
different evolutionary stages and metallicities. These questions range from the
origin of these fields to their true incidence rate throughout the stellar population
and the dependence on metallicity. Magnetic fields, although currently often excluded
from stellar evolution models, play an important role in stellar evolution. Connecting
the surface fields to internal fields through asteroseismology will instigate
a new era of understanding stellar evolution and the transport of angular momentum
and chemical elements throughout stellar interiors, also impacting our understanding
of star-planet interactions and stellar remnants. Polarimetry is also an under-utilized
tool to observationally constrain the mode identification of nonradial oscillations,
which lies at the basis of accurate asteroseismic parameter estimation at percentage-level
for stellar radii, masses, ages, internal rotation, and magnetic field strengths.
Combining strong constraints on mode identification and surface magnetic properties
through the acquisition of time-resolved, high-resolution and high-signal-to-noise
(S/N) spectro-polarimetry and spectroscopy promises to bring leaps forward in
our understanding of stellar structure, particularly when combined with long-term
space photometric data from past, current, and future missions.
article_number: '2512.15170'
article_processing_charge: No
arxiv: 1
author:
- first_name: J.
full_name: Vandersnickt, J.
last_name: Vandersnickt
- first_name: R. Ochoa
full_name: Armenta, R. Ochoa
last_name: Armenta
- first_name: V.
full_name: Vanlaer, V.
last_name: Vanlaer
- first_name: A. David-Uraz
full_name: A. David-Uraz, A. David-Uraz
last_name: A. David-Uraz
- first_name: C.
full_name: Aerts, C.
last_name: Aerts
- first_name: S. B.
full_name: Das, S. B.
last_name: Das
- first_name: J. -C.
full_name: Bouret, J. -C.
last_name: Bouret
- first_name: D. M.
full_name: Bowman, D. M.
last_name: Bowman
- first_name: Lisa Annabelle
full_name: Bugnet, Lisa Annabelle
id: d9edb345-f866-11ec-9b37-d119b5234501
last_name: Bugnet
orcid: 0000-0003-0142-4000
- first_name: V.
full_name: Khalack, V.
last_name: Khalack
- first_name: J. Labadie-Bartz
full_name: J. Labadie-Bartz, J. Labadie-Bartz
last_name: J. Labadie-Bartz
- first_name: S.
full_name: Mathis, S.
last_name: Mathis
- first_name: Y.
full_name: Nazé, Y.
last_name: Nazé
- first_name: C.
full_name: Neiner, C.
last_name: Neiner
- first_name: P.
full_name: Petit, P.
last_name: Petit
- first_name: V.
full_name: Petit, V.
last_name: Petit
- first_name: K. Thomson-Paressant
full_name: K. Thomson-Paressant, K. Thomson-Paressant
last_name: K. Thomson-Paressant
- first_name: T. Van
full_name: Doorsselaere, T. Van
last_name: Doorsselaere
- first_name: M.
full_name: Vanrespaille, M.
last_name: Vanrespaille
citation:
ama: Vandersnickt J, Armenta RO, Vanlaer V, et al. Expanding stellar horizons with
polarized light. arXiv. doi:10.48550/arXiv.2512.15170
apa: Vandersnickt, J., Armenta, R. O., Vanlaer, V., A. David-Uraz, A. D.-U., Aerts,
C., Das, S. B., … Vanrespaille, M. (n.d.). Expanding stellar horizons with polarized
light. arXiv. https://doi.org/10.48550/arXiv.2512.15170
chicago: Vandersnickt, J., R. Ochoa Armenta, V. Vanlaer, A. David-Uraz A. David-Uraz,
C. Aerts, S. B. Das, J. -C. Bouret, et al. “Expanding Stellar Horizons with Polarized
Light.” ArXiv, n.d. https://doi.org/10.48550/arXiv.2512.15170.
ieee: J. Vandersnickt et al., “Expanding stellar horizons with polarized
light,” arXiv. .
ista: Vandersnickt J, Armenta RO, Vanlaer V, A. David-Uraz AD-U, Aerts C, Das SB,
Bouret J-C, Bowman DM, Bugnet LA, Khalack V, J. Labadie-Bartz JL-B, Mathis S,
Nazé Y, Neiner C, Petit P, Petit V, K. Thomson-Paressant KT-P, Doorsselaere TV,
Vanrespaille M. Expanding stellar horizons with polarized light. arXiv, 2512.15170.
mla: Vandersnickt, J., et al. “Expanding Stellar Horizons with Polarized Light.”
ArXiv, 2512.15170, doi:10.48550/arXiv.2512.15170.
short: J. Vandersnickt, R.O. Armenta, V. Vanlaer, A.D.-U. A. David-Uraz, C. Aerts,
S.B. Das, J.-C. Bouret, D.M. Bowman, L.A. Bugnet, V. Khalack, J.L.-B. J. Labadie-Bartz,
S. Mathis, Y. Nazé, C. Neiner, P. Petit, V. Petit, K.T.-P. K. Thomson-Paressant,
T.V. Doorsselaere, M. Vanrespaille, ArXiv (n.d.).
date_created: 2026-02-17T13:53:50Z
date_published: 2025-12-17T00:00:00Z
date_updated: 2026-04-07T06:00:40Z
day: '17'
department:
- _id: LiBu
doi: 10.48550/arXiv.2512.15170
external_id:
arxiv:
- '2512.15170'
fulldoi: https://doi.org/10.48550/arXiv.2512.15170
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2512.15170
month: '12'
oa: 1
oa_version: Preprint
publication: arXiv
publication_status: submitted
status: public
title: Expanding stellar horizons with polarized light
type: preprint
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2025'
...
---
DOAJ_listed: '1'
OA_place: publisher
OA_type: gold
PlanS_conform: '1'
_id: '21317'
abstract:
- lang: eng
text: Accreting white dwarfs (WDs) in close binary systems, commonly known as cataclysmic
variables (CVs), with orbital periods below the canonical period minimum (≈80
minutes) are rare. Such short periods can only be reached if the donor star in
the CV is either significantly evolved before initiating mass transfer to the
WD or is metal-poor. We present optical photometry and spectroscopy of Gaia19bxc,
a high-amplitude variable identified as a polar CV with an exceptionally short
orbital period of 64.42 minutes—well below the canonical CV period minimum. High-speed
photometry confirms persistent double-peaked variability consistent with cyclotron
beaming, thus indicating the presence of a magnetic WD. Phase-resolved Keck/Low-Resolution
Imaging Spectrometer (LRIS) spectroscopy reveals strong hydrogen and helium emission
lines but no donor features, indicating the accretor is a magnetic WD and the
donor is hydrogen-rich, but cold and faint. The absence of a detectable donor
and the low inferred temperature (≲3500 K) disfavor an evolved donor scenario.
Instead, the short period and the system’s halo-like kinematics suggest Gaia19bxc
may be the first known metal-poor polar. Because metal-poor donors are more compact
than solar-metallicity donors of the same mass, they can reach shorter minimum
periods. Gaia19bxc is one of only a handful of known metal-poor CVs below the
canonical period minimum and has the shortest period of any such magnetic system
discovered to date.
acknowledgement: "Based on observations obtained with the Samuel Oschin Telescope
48 inch and the 60 inch Telescope at the Palomar Observatory as part of the Zwicky
Transient Facility project. ZTF is supported by the National Science Foundation
under grants No. AST-1440341 and AST-2034437 and a collaboration including current
partners Caltech, IPAC, the Weizmann Institute of Science, the Oskar Klein Center
at Stockholm University, the University of Maryland, Deutsches Elektronen-Synchrotron
and Humboldt University, the TANGO Consortium of Taiwan, the University of Wisconsin
at Milwaukee, Trinity College Dublin, Lawrence Livermore National Laboratories,
IN2P3, University of Warwick, Ruhr University Bochum, Northwestern University and
former partners the University of Washington, Los Alamos National Laboratories,
and Lawrence Berkeley National Laboratories. Operations are conducted by COO, IPAC,
and UW. This work has made use of data from the European Space Agency (ESA) mission
Gaia (https://www.cosmos.esa.int/gaia), processed by the Gaia Data Processing and
Analysis Consortium (DPAC; https://www.cosmos.esa.int/web/gaia/dpac/consortium).
Funding for the DPAC has been provided by national institutions, in particular the
institutions participating in the Gaia Multilateral Agreement. Some of the data
presented herein were obtained at Keck Observatory, which is a private 501(c)3 nonprofit
organization operated as a scientific partnership among the California Institute
of Technology, the University of California, and the National Aeronautics and Space
Administration. The Observatory was made possible by the generous financial support
of the W. M. Keck Foundation. We wish to recognize and acknowledge the very significant
cultural role and reverence that the summit of Maunakea has always had within the
Native Hawaiian community. We are most fortunate to have had the opportunity to
conduct observations from this mountain. We are grateful to the staff of the Palomar
and Keck Observatories for their work in helping us carry out our observations.\r\n\r\nI.G.
acknowledges support from Kazan Federal University. A.C.R. acknowledges support
from the National Science Foundation via an NSF Graduate Research Fellowship. We
thank the anonymous referee for useful comments and suggestions, which contributed
to the improvement of this manuscript."
article_number: L57
article_processing_charge: Yes
article_type: original
arxiv: 1
author:
- first_name: Ilkham
full_name: Galiullin, Ilkham
last_name: Galiullin
- first_name: Antonio C.
full_name: Rodriguez, Antonio C.
last_name: Rodriguez
- first_name: Kareem
full_name: El-Badry, Kareem
last_name: El-Badry
- first_name: Ilaria
full_name: Caiazzo, Ilaria
id: 8ae5b6e7-2a03-11ee-914d-b58ed7a3b47d
last_name: Caiazzo
orcid: 0000-0002-4770-5388
- first_name: Paula
full_name: Szkody, Paula
last_name: Szkody
- first_name: Pranav
full_name: Nagarajan, Pranav
last_name: Nagarajan
- first_name: Samuel
full_name: Whitebook, Samuel
last_name: Whitebook
citation:
ama: Galiullin I, Rodriguez AC, El-Badry K, et al. Optical spectroscopy of the most
compact accreting binary harboring a magnetic White Dwarf and a hydrogen-rich
donor. The Astrophysical Journal Letters. 2025;990(2). doi:10.3847/2041-8213/adff82
apa: Galiullin, I., Rodriguez, A. C., El-Badry, K., Caiazzo, I., Szkody, P., Nagarajan,
P., & Whitebook, S. (2025). Optical spectroscopy of the most compact accreting
binary harboring a magnetic White Dwarf and a hydrogen-rich donor. The Astrophysical
Journal Letters. IOP Publishing. https://doi.org/10.3847/2041-8213/adff82
chicago: Galiullin, Ilkham, Antonio C. Rodriguez, Kareem El-Badry, Ilaria Caiazzo,
Paula Szkody, Pranav Nagarajan, and Samuel Whitebook. “Optical Spectroscopy of
the Most Compact Accreting Binary Harboring a Magnetic White Dwarf and a Hydrogen-Rich
Donor.” The Astrophysical Journal Letters. IOP Publishing, 2025. https://doi.org/10.3847/2041-8213/adff82.
ieee: I. Galiullin et al., “Optical spectroscopy of the most compact accreting
binary harboring a magnetic White Dwarf and a hydrogen-rich donor,” The Astrophysical
Journal Letters, vol. 990, no. 2. IOP Publishing, 2025.
ista: Galiullin I, Rodriguez AC, El-Badry K, Caiazzo I, Szkody P, Nagarajan P, Whitebook
S. 2025. Optical spectroscopy of the most compact accreting binary harboring a
magnetic White Dwarf and a hydrogen-rich donor. The Astrophysical Journal Letters.
990(2), L57.
mla: Galiullin, Ilkham, et al. “Optical Spectroscopy of the Most Compact Accreting
Binary Harboring a Magnetic White Dwarf and a Hydrogen-Rich Donor.” The Astrophysical
Journal Letters, vol. 990, no. 2, L57, IOP Publishing, 2025, doi:10.3847/2041-8213/adff82.
short: I. Galiullin, A.C. Rodriguez, K. El-Badry, I. Caiazzo, P. Szkody, P. Nagarajan,
S. Whitebook, The Astrophysical Journal Letters 990 (2025).
date_created: 2026-02-18T10:17:04Z
date_published: 2025-09-08T00:00:00Z
date_updated: 2026-02-19T07:27:01Z
day: '08'
ddc:
- '520'
department:
- _id: IlCa
doi: 10.3847/2041-8213/adff82
external_id:
arxiv:
- '2508.20170'
file:
- access_level: open_access
checksum: f76556d129aa0e9facc85602b0b5b54d
content_type: application/pdf
creator: dernst
date_created: 2026-02-19T07:24:10Z
date_updated: 2026-02-19T07:24:10Z
file_id: '21329'
file_name: 2025_AstrophysicalJournal_Galiullin.pdf
file_size: 3772189
relation: main_file
success: 1
file_date_updated: 2026-02-19T07:24:10Z
fulldoi: https://doi.org/10.3847/2041-8213/adff82
has_accepted_license: '1'
intvolume: ' 990'
issue: '2'
language:
- iso: eng
month: '09'
oa: 1
oa_version: Published Version
publication: The 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: Optical spectroscopy of the most compact accreting binary harboring a magnetic
White Dwarf and a hydrogen-rich donor
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: 990
year: '2025'
...
---
OA_place: repository
OA_type: green
_id: '21318'
abstract:
- lang: eng
text: Matter waves have been observed in double-slit experiments with microscopic
objects, such as atoms or molecules. The wave function describing the motion of
these objects must extend over a distance comparable to the slit separation, much
larger than the characteristic size of the objects. Preparing such states for
more massive objects, such as mechanical oscillators, remains an outstanding challenge.
Here we delocalize the quantum ground state of an optically levitated nanosphere
by modulating the stiffness of the confining potential. We show a more than threefold
increase of the initial coherence length, which corresponds to mechanical momentum
squeezing of more than 7 dB. Our work is a stepping stone toward the generation
of coherence lengths comparable to the object size, a crucial regime for macroscopic
quantum experiments.
article_number: '083601'
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: M.
full_name: Rossi, M.
last_name: Rossi
- first_name: Andrei
full_name: Militaru, Andrei
id: d67706f8-8eb1-11ee-ad1b-9c30dfa19e0b
last_name: Militaru
- first_name: N.
full_name: Carlon Zambon, N.
last_name: Carlon Zambon
- first_name: A.
full_name: Riera-Campeny, A.
last_name: Riera-Campeny
- first_name: O.
full_name: Romero-Isart, O.
last_name: Romero-Isart
- first_name: M.
full_name: Frimmer, M.
last_name: Frimmer
- first_name: L.
full_name: Novotny, L.
last_name: Novotny
citation:
ama: Rossi M, Militaru A, Carlon Zambon N, et al. Quantum delocalization of a levitated
nanoparticle. Physical Review Letters. 2025;135(8). doi:10.1103/2yzc-fsm3
apa: Rossi, M., Militaru, A., Carlon Zambon, N., Riera-Campeny, A., Romero-Isart,
O., Frimmer, M., & Novotny, L. (2025). Quantum delocalization of a levitated
nanoparticle. Physical Review Letters. American Physical Society. https://doi.org/10.1103/2yzc-fsm3
chicago: Rossi, M., Andrei Militaru, N. Carlon Zambon, A. Riera-Campeny, O. Romero-Isart,
M. Frimmer, and L. Novotny. “Quantum Delocalization of a Levitated Nanoparticle.”
Physical Review Letters. American Physical Society, 2025. https://doi.org/10.1103/2yzc-fsm3.
ieee: M. Rossi et al., “Quantum delocalization of a levitated nanoparticle,”
Physical Review Letters, vol. 135, no. 8. American Physical Society, 2025.
ista: Rossi M, Militaru A, Carlon Zambon N, Riera-Campeny A, Romero-Isart O, Frimmer
M, Novotny L. 2025. Quantum delocalization of a levitated nanoparticle. Physical
Review Letters. 135(8), 083601.
mla: Rossi, M., et al. “Quantum Delocalization of a Levitated Nanoparticle.” Physical
Review Letters, vol. 135, no. 8, 083601, American Physical Society, 2025,
doi:10.1103/2yzc-fsm3.
short: M. Rossi, A. Militaru, N. Carlon Zambon, A. Riera-Campeny, O. Romero-Isart,
M. Frimmer, L. Novotny, Physical Review Letters 135 (2025).
date_created: 2026-02-18T10:19:30Z
date_published: 2025-08-19T00:00:00Z
date_updated: 2026-02-24T07:03:57Z
day: '19'
department:
- _id: JoFi
doi: 10.1103/2yzc-fsm3
external_id:
arxiv:
- '2408.01264'
pmid:
- '40929305'
fulldoi: https://doi.org/10.1103/2yzc-fsm3
intvolume: ' 135'
issue: '8'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2408.01264
month: '08'
oa: 1
oa_version: Preprint
pmid: 1
publication: Physical Review Letters
publication_identifier:
eissn:
- 1079-7114
issn:
- 0031-9007
publication_status: published
publisher: American Physical Society
quality_controlled: '1'
status: public
title: Quantum delocalization of a levitated nanoparticle
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 135
year: '2025'
...
---
OA_place: publisher
OA_type: hybrid
PlanS_conform: '1'
_id: '21321'
abstract:
- lang: eng
text: 'The development of cost-effective and high-performance thermoelectric (TE)
materials faces significant challenges, particularly in improving the properties
of promising copper-based TE materials such as Cu3SbSe4, which are limited by
their poor electrical conductivity. This study presents a detailed comparative
analysis of three strategies to promote the electrical transport properties of
Cu3SbSe4 through Sn doping: conventional Sn atomic doping, surface treatment with
SnSe molecular complexes, and blending with SnSe nanocrystals to form nanocomposites,
all followed by annealing and hot pressing under identical conditions. Our results
reveal that a surface treatment using SnSe molecular complexes significantly enhances
TE performance over atomic doping and nanocomposite formation, achieving a power
factor of 1.1 mW·m−1·K−2 and a maximum dimensionless figure of merit zT value
of 0.80 at 640 K, representing an excellent performance among Cu3SbSe4-based materials
produced via solution-processing methods. This work highlights the effectiveness
of surface engineering in optimizing the transport properties of nanostructured
materials, demonstrating the versatility and cost-efficiency of solution-based
technologies in the development of advanced nanostructured materials for application
in the field of TE among others.'
acknowledgement: Y. L. acknowledges funding from the National Natural Science Foundation
of China (No. 22209034), the Innovation and Entrepreneurship Project of Overseas
Returnees in Anhui Province (No. 2022LCX002), and the Fundamental Research Funds
for the Central Universities (No. JZ2024HGTB0239). K. H. L. acknowledges financial
support from the National Natural Science Foundation of China (No. 22208293). M.
I. acknowledge financial support from ISTA and the Werner Siemens Foundation. M.
H. acknowledges funding from Australian Research Council (No. FT230100316). L. L.
H. and S. H. W. acknowledge the Fundamental Research Funds for the Central Universities
(Nos. JZ2023HGTA0179 and JZ2024HGTA0170).
article_number: '94907072'
article_processing_charge: Yes (in subscription journal)
article_type: original
author:
- first_name: Shanshan
full_name: Xiao, Shanshan
last_name: Xiao
- first_name: Mingjun
full_name: Zhao, Mingjun
last_name: Zhao
- first_name: Mingquan
full_name: Li, Mingquan
last_name: Li
- first_name: Shanhong
full_name: Wan, Shanhong
last_name: Wan
- first_name: Aziz
full_name: Genç, Aziz
last_name: Genç
- first_name: Lulu
full_name: Huang, Lulu
last_name: Huang
- first_name: Lei
full_name: Chen, Lei
last_name: Chen
- first_name: Yu
full_name: Zhang, Yu
last_name: Zhang
- first_name: Maria
full_name: Ibáñez, Maria
id: 43C61214-F248-11E8-B48F-1D18A9856A87
last_name: Ibáñez
orcid: 0000-0001-5013-2843
- first_name: Khak Ho
full_name: Lim, Khak Ho
last_name: Lim
- first_name: Min
full_name: Hong, Min
last_name: Hong
- first_name: Yu
full_name: Liu, Yu
last_name: Liu
- first_name: Andreu
full_name: Cabot, Andreu
last_name: Cabot
citation:
ama: 'Xiao S, Zhao M, Li M, et al. Band and defect engineering in solution-processed
nanocrystal building blocks to promote transport properties in nanomaterials:
The case of thermoelectric Cu 3SbSe 4.
Nano Research. 2025;18(1). doi:10.26599/nr.2025.94907072'
apa: 'Xiao, S., Zhao, M., Li, M., Wan, S., Genç, A., Huang, L., … Cabot, A. (2025).
Band and defect engineering in solution-processed nanocrystal building blocks
to promote transport properties in nanomaterials: The case of thermoelectric Cu
3SbSe 4. Nano Research. Tsinghua
University Press. https://doi.org/10.26599/nr.2025.94907072'
chicago: 'Xiao, Shanshan, Mingjun Zhao, Mingquan Li, Shanhong Wan, Aziz Genç, Lulu
Huang, Lei Chen, et al. “Band and Defect Engineering in Solution-Processed Nanocrystal
Building Blocks to Promote Transport Properties in Nanomaterials: The Case of
Thermoelectric Cu 3SbSe 4.” Nano
Research. Tsinghua University Press, 2025. https://doi.org/10.26599/nr.2025.94907072.'
ieee: 'S. Xiao et al., “Band and defect engineering in solution-processed
nanocrystal building blocks to promote transport properties in nanomaterials:
The case of thermoelectric Cu 3SbSe 4,”
Nano Research, vol. 18, no. 1. Tsinghua University Press, 2025.'
ista: 'Xiao S, Zhao M, Li M, Wan S, Genç A, Huang L, Chen L, Zhang Y, Ibáñez M,
Lim KH, Hong M, Liu Y, Cabot A. 2025. Band and defect engineering in solution-processed
nanocrystal building blocks to promote transport properties in nanomaterials:
The case of thermoelectric Cu 3SbSe 4.
Nano Research. 18(1), 94907072.'
mla: 'Xiao, Shanshan, et al. “Band and Defect Engineering in Solution-Processed
Nanocrystal Building Blocks to Promote Transport Properties in Nanomaterials:
The Case of Thermoelectric Cu 3SbSe 4.”
Nano Research, vol. 18, no. 1, 94907072, Tsinghua University Press, 2025,
doi:10.26599/nr.2025.94907072.'
short: S. Xiao, M. Zhao, M. Li, S. Wan, A. Genç, L. Huang, L. Chen, Y. Zhang, M.
Ibáñez, K.H. Lim, M. Hong, Y. Liu, A. Cabot, Nano Research 18 (2025).
date_created: 2026-02-18T10:45:06Z
date_published: 2025-01-01T00:00:00Z
date_updated: 2026-02-19T07:32:22Z
day: '01'
ddc:
- '540'
department:
- _id: MaIb
doi: 10.26599/nr.2025.94907072
file:
- access_level: open_access
checksum: aa531f1363538fece12ecfad83456b65
content_type: application/pdf
creator: dernst
date_created: 2026-02-19T07:31:15Z
date_updated: 2026-02-19T07:31:15Z
file_id: '21330'
file_name: 2025_NanoResearch_Xiao.pdf
file_size: 27740524
relation: main_file
success: 1
file_date_updated: 2026-02-19T07:31:15Z
fulldoi: https://doi.org/10.26599/nr.2025.94907072
has_accepted_license: '1'
intvolume: ' 18'
issue: '1'
language:
- iso: eng
month: '01'
oa: 1
oa_version: Published Version
project:
- _id: 9B8F7476-BA93-11EA-9121-9846C619BF3A
name: 'HighTE: The Werner Siemens Laboratory for the High Throughput Discovery of
Semiconductors for Waste Heat Recovery'
publication: Nano Research
publication_identifier:
eissn:
- 1998-0000
issn:
- 1998-0124
publication_status: published
publisher: Tsinghua University Press
status: public
title: 'Band and defect engineering in solution-processed nanocrystal building blocks
to promote transport properties in nanomaterials: The case of thermoelectric Cu 3SbSe 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: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 18
year: '2025'
...
---
OA_place: repository
OA_type: green
_id: '21322'
abstract:
- lang: eng
text: Habitat fragmentation poses a significant risk to population survival, causing
both demographic stochasticity and genetic drift within local populations to increase,
thereby increasing genetic load. Higher load causes population numbers to decline,
which reduces the efficiency of selection and further increases load, resulting
in a positive feedback that may drive entire populations to extinction. Here,
we investigate this eco-evolutionary feedback in a metapopulation consisting of
local demes connected via migration, with individuals subject to deleterious mutation
at a large number of loci. We first analyze the determinants of load under soft
selection, where population sizes are fixed, and then build on this to understand
hard selection, where population sizes and load coevolve. We show that under soft
selection, very little gene flow (less than one migrant per generation) is enough
to prevent fixation of deleterious alleles. By contrast, much higher levels of
migration are required to mitigate load and prevent extinction when selection
is hard, with critical migration thresholds for metapopulation persistence increasing
sharply as the genome-wide deleterious mutation rate becomes comparable to the
baseline population growth rate. Moreover, critical migration thresholds are highest
if deleterious mutations have intermediate selection coefficients but lower if
alleles are predominantly recessive rather than additive (due to more efficient
purging of recessive load within local populations). Our analysis is based on
a combination of analytical approximations and simulations, allowing for a more
comprehensive understanding of the factors influencing load and extinction in
fragmented populations.
acknowledgement: 'This research was partially funded by the Austrian Science Fund
(FWF P-32896B) and DOC Fellowships of the Austrian Academy of Sciences: grants 26380
(O.O.) and 26293 (K.K.). We thank Nick Barton for useful comments on the chapter
in O.O.’s thesis that led to this article.'
article_processing_charge: No
article_type: original
author:
- first_name: Oluwafunmilola O
full_name: Olusanya, Oluwafunmilola O
id: 41AD96DC-F248-11E8-B48F-1D18A9856A87
last_name: Olusanya
orcid: 0000-0003-1971-8314
- first_name: Kseniia
full_name: Khudiakova, Kseniia
id: 4E6DC800-AE37-11E9-AC72-31CAE5697425
last_name: Khudiakova
orcid: 0000-0002-6246-1465
- first_name: Himani
full_name: Sachdeva, Himani
id: 42377A0A-F248-11E8-B48F-1D18A9856A87
last_name: Sachdeva
citation:
ama: Olusanya OO, Khudiakova K, Sachdeva H. Genetic load, eco-evolutionary feedback,
and extinction in metapopulations. The American Naturalist. 2025;205(6):617-636.
doi:10.1086/735562
apa: Olusanya, O. O., Khudiakova, K., & Sachdeva, H. (2025). Genetic load, eco-evolutionary
feedback, and extinction in metapopulations. The American Naturalist. University
of Chicago Press. https://doi.org/10.1086/735562
chicago: Olusanya, Oluwafunmilola O, Kseniia Khudiakova, and Himani Sachdeva. “Genetic
Load, Eco-Evolutionary Feedback, and Extinction in Metapopulations.” The American
Naturalist. University of Chicago Press, 2025. https://doi.org/10.1086/735562.
ieee: O. O. Olusanya, K. Khudiakova, and H. Sachdeva, “Genetic load, eco-evolutionary
feedback, and extinction in metapopulations,” The American Naturalist,
vol. 205, no. 6. University of Chicago Press, pp. 617–636, 2025.
ista: Olusanya OO, Khudiakova K, Sachdeva H. 2025. Genetic load, eco-evolutionary
feedback, and extinction in metapopulations. The American Naturalist. 205(6),
617–636.
mla: Olusanya, Oluwafunmilola O., et al. “Genetic Load, Eco-Evolutionary Feedback,
and Extinction in Metapopulations.” The American Naturalist, vol. 205,
no. 6, University of Chicago Press, 2025, pp. 617–36, doi:10.1086/735562.
short: O.O. Olusanya, K. Khudiakova, H. Sachdeva, The American Naturalist 205 (2025)
617–636.
corr_author: '1'
date_created: 2026-02-18T10:47:18Z
date_published: 2025-06-01T00:00:00Z
date_updated: 2026-04-07T08:45:14Z
day: '01'
department:
- _id: JaMa
- _id: NiBa
doi: 10.1086/735562
external_id:
pmid:
- '40446297 '
fulldoi: https://doi.org/10.1086/735562
intvolume: ' 205'
issue: '6'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.1101/2023.12.02.569702
month: '06'
oa: 1
oa_version: Preprint
page: 617-636
pmid: 1
project:
- _id: c08d3278-5a5b-11eb-8a69-fdb09b55f4b8
grant_number: P32896
name: Causes and consequences of population fragmentation
- _id: 34c872fe-11ca-11ed-8bc3-8534b82131e6
grant_number: '26380'
name: Polygenic Adaptation in a Metapopulation
- _id: 34d33d68-11ca-11ed-8bc3-ec13763c0ca8
grant_number: '26293'
name: The impact of deleterious mutations on small populations
publication: The American Naturalist
publication_identifier:
eissn:
- 1537-5323
issn:
- 0003-0147
publication_status: published
publisher: University of Chicago Press
quality_controlled: '1'
related_material:
record:
- id: '14732'
relation: earlier_version
status: public
scopus_import: '1'
status: public
title: Genetic load, eco-evolutionary feedback, and extinction in metapopulations
type: journal_article
user_id: ba8df636-2132-11f1-aed0-ed93e2281fdd
volume: 205
year: '2025'
...
---
OA_place: repository
OA_type: green
_id: '21323'
abstract:
- lang: eng
text: We present a unifying framework for proving the knowledge-soundness of KZG-like
polynomial commitment schemes, encompassing both univariate and multivariate variants.
By conceptualizing the proof technique of Lipmaa, Parisella, and Siim for the
univariate KZG scheme (EUROCRYPT 2024), we present tools and falsifiable hardness
assumptions that permit black-box extraction of the multivariate KZG scheme. Central
to our approach is the notion of a canonical Proof-of-Knowledge of a Polynomial
(PoKoP) of a polynomial commitment scheme, which we use to capture the extractability
notion required in constructions of practical zk-SNARKs. We further present an
explicit polynomial decomposition lemma for multivariate polynomials, enabling
a more direct analysis of interpolating extractors and bridging the gap between
univariate and multivariate commitments. Our results provide the first standard-model
proofs of extractability for the multivariate KZG scheme and many of its variants
under falsifiable assumptions.
acknowledgement: Juraj Belohorec, Pavel Hubáček, and Kristýna Mašková were partially
supported by the Academy of Sciences of the Czech Republic (RVO 67985840), Czech
Science Foundation GAČR grant No. 25-16311S, and by Zircuit. Pavel Dvořák was supported
by Czech Science Foundation GAČR grant No. 22-14872O. Juraj Belohorec and Kristýna
Mašková were supported by the grant SVV–2025–260822.
alternative_title:
- LNCS
article_processing_charge: No
author:
- first_name: Juraj
full_name: Belohorec, Juraj
last_name: Belohorec
- first_name: Pavel
full_name: Dvořák, Pavel
last_name: Dvořák
- first_name: Charlotte
full_name: Hoffmann, Charlotte
id: 0f78d746-dc7d-11ea-9b2f-83f92091afe7
last_name: Hoffmann
orcid: 0000-0003-2027-5549
- first_name: Pavel
full_name: Hubáček, Pavel
last_name: Hubáček
- first_name: Kristýna
full_name: Mašková, Kristýna
last_name: Mašková
- first_name: Martin
full_name: Pastyřík, Martin
last_name: Pastyřík
citation:
ama: 'Belohorec J, Dvořák P, Hoffmann C, Hubáček P, Mašková K, Pastyřík M. On extractability
of the KZG family of polynomial commitment schemes. In: 45th Annual International
Cryptology Conference. Vol 16005. Springer Nature; 2025:584-616. doi:10.1007/978-3-032-01887-8_19'
apa: 'Belohorec, J., Dvořák, P., Hoffmann, C., Hubáček, P., Mašková, K., & Pastyřík,
M. (2025). On extractability of the KZG family of polynomial commitment schemes.
In 45th Annual International Cryptology Conference (Vol. 16005, pp. 584–616).
Santa Barbara, CA, United States: Springer Nature. https://doi.org/10.1007/978-3-032-01887-8_19'
chicago: Belohorec, Juraj, Pavel Dvořák, Charlotte Hoffmann, Pavel Hubáček, Kristýna
Mašková, and Martin Pastyřík. “On Extractability of the KZG Family of Polynomial
Commitment Schemes.” In 45th Annual International Cryptology Conference,
16005:584–616. Springer Nature, 2025. https://doi.org/10.1007/978-3-032-01887-8_19.
ieee: J. Belohorec, P. Dvořák, C. Hoffmann, P. Hubáček, K. Mašková, and M. Pastyřík,
“On extractability of the KZG family of polynomial commitment schemes,” in 45th
Annual International Cryptology Conference, Santa Barbara, CA, United States,
2025, vol. 16005, pp. 584–616.
ista: 'Belohorec J, Dvořák P, Hoffmann C, Hubáček P, Mašková K, Pastyřík M. 2025.
On extractability of the KZG family of polynomial commitment schemes. 45th Annual
International Cryptology Conference. CRYPTO: International Cryptology Conference,
LNCS, vol. 16005, 584–616.'
mla: Belohorec, Juraj, et al. “On Extractability of the KZG Family of Polynomial
Commitment Schemes.” 45th Annual International Cryptology Conference, vol.
16005, Springer Nature, 2025, pp. 584–616, doi:10.1007/978-3-032-01887-8_19.
short: J. Belohorec, P. Dvořák, C. Hoffmann, P. Hubáček, K. Mašková, M. Pastyřík,
in:, 45th Annual International Cryptology Conference, Springer Nature, 2025, pp.
584–616.
conference:
end_date: 2025-08-221
location: Santa Barbara, CA, United States
name: 'CRYPTO: International Cryptology Conference'
start_date: 2025-08-17
date_created: 2026-02-18T10:59:58Z
date_published: 2025-08-17T00:00:00Z
date_updated: 2026-02-19T07:50:33Z
day: '17'
department:
- _id: KrPi
doi: 10.1007/978-3-032-01887-8_19
fulldoi: https://doi.org/10.1007/978-3-032-01887-8_19
intvolume: ' 16005'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://eprint.iacr.org/2025/514
month: '08'
oa: 1
oa_version: Preprint
page: 584-616
publication: 45th Annual International Cryptology Conference
publication_identifier:
eisbn:
- '9783032018878'
eissn:
- 1611-3349
isbn:
- '9783032018861'
issn:
- 0302-9743
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
status: public
title: On extractability of the KZG family of polynomial commitment schemes
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 16005
year: '2025'
...
---
OA_place: publisher
OA_type: gold
_id: '21325'
abstract:
- lang: eng
text: Test-time training (TTT) methods explicitly update the weights of a model
to adapt to the specific test instance, and they have found success in a variety
of settings, including most recently language modeling and reasoning. To demystify
this success, we investigate a gradient-based TTT algorithm for in-context learning,
where we train a transformer model on the in-context demonstrations provided in
the test prompt. Specifically, we provide a comprehensive theoretical characterization
of linear transformers when the update rule is a single gradient step. Our theory
(i) delineates the role of alignment between pretraining distribution and target
task, (ii) demystifies how TTT can alleviate distribution shift, and (iii) quantifies
the sample complexity of TTT including how it can significantly reduce the eventual
sample size required for in-context learning. As our empirical contribution, we
study the benefits of TTT for TabPFN, a tabular foundation model. In line with
our theory, we demonstrate that TTT significantly reduces the required sample
size for tabular classification (3 to 5 times fewer) unlocking substantial inference
efficiency with a negligible training cost.
acknowledgement: "H.A.G., M.E.I., X.Z., and S.O. were supported in part by the NSF
grants CCF2046816, CCF-2403075, CCF-2008020, and the Office of Naval Research grant
N000142412289.\r\nM. M. is funded by the European Union (ERC, INF2 , project number
101161364). Views and opinions expressed are, however, those of the author(s) only
and do not necessarily\r\nreflect those of the European Union or the European Research
Council Executive Agency. Neither the European Union nor the granting authority
can be held responsible for them. M.S. is supported by the Packard Fellowship in
Science and Engineering, a Sloan Research Fellowship in Mathematics, an NSF-CAREER
under award #1846369, DARPA FastNICS program, and NSF-CIF awards #1813877 and #2008443,
and NIH DP2LM014564-01. The authors also\r\nacknowledge further support from Open
Philanthropy, OpenAI, Amazon Research, Google Research, and Microsoft Research."
alternative_title:
- PMLR
article_processing_charge: No
author:
- first_name: Halil Alperen
full_name: Gozeten, Halil Alperen
last_name: Gozeten
- first_name: Muhammed Emrullah
full_name: Ildiz, Muhammed Emrullah
last_name: Ildiz
- first_name: Xuechen
full_name: Zhang, Xuechen
last_name: Zhang
- first_name: Mahdi
full_name: Soltanolkotabi, Mahdi
last_name: Soltanolkotabi
- first_name: Marco
full_name: Mondelli, Marco
id: 27EB676C-8706-11E9-9510-7717E6697425
last_name: Mondelli
orcid: 0000-0002-3242-7020
- first_name: Samet
full_name: Oymak, Samet
last_name: Oymak
citation:
ama: 'Gozeten HA, Ildiz ME, Zhang X, Soltanolkotabi M, Mondelli M, Oymak S. Test-time
training provably improves transformers as in-context learners. In: Proceedings
of the 42nd International Conference on Machine Learning. Vol 267. ML Research
Press; 2025:20266-20295.'
apa: 'Gozeten, H. A., Ildiz, M. E., Zhang, X., Soltanolkotabi, M., Mondelli, M.,
& Oymak, S. (2025). Test-time training provably improves transformers as in-context
learners. In Proceedings of the 42nd International Conference on Machine Learning
(Vol. 267, pp. 20266–20295). Vancouver, Canada: ML Research Press.'
chicago: Gozeten, Halil Alperen, Muhammed Emrullah Ildiz, Xuechen Zhang, Mahdi Soltanolkotabi,
Marco Mondelli, and Samet Oymak. “Test-Time Training Provably Improves Transformers
as in-Context Learners.” In Proceedings of the 42nd International Conference
on Machine Learning, 267:20266–95. ML Research Press, 2025.
ieee: H. A. Gozeten, M. E. Ildiz, X. Zhang, M. Soltanolkotabi, M. Mondelli, and
S. Oymak, “Test-time training provably improves transformers as in-context learners,”
in Proceedings of the 42nd International Conference on Machine Learning,
Vancouver, Canada, 2025, vol. 267, pp. 20266–20295.
ista: 'Gozeten HA, Ildiz ME, Zhang X, Soltanolkotabi M, Mondelli M, Oymak S. 2025.
Test-time training provably improves transformers as in-context learners. Proceedings
of the 42nd International Conference on Machine Learning. ICML: International
Conference on Machine Learning, PMLR, vol. 267, 20266–20295.'
mla: Gozeten, Halil Alperen, et al. “Test-Time Training Provably Improves Transformers
as in-Context Learners.” Proceedings of the 42nd International Conference on
Machine Learning, vol. 267, ML Research Press, 2025, pp. 20266–95.
short: H.A. Gozeten, M.E. Ildiz, X. Zhang, M. Soltanolkotabi, M. Mondelli, S. Oymak,
in:, Proceedings of the 42nd International Conference on Machine Learning, ML
Research Press, 2025, pp. 20266–20295.
conference:
end_date: 2025-07-19
location: Vancouver, Canada
name: 'ICML: International Conference on Machine Learning'
start_date: 2025-07-13
date_created: 2026-02-18T12:00:44Z
date_published: 2025-11-30T00:00:00Z
date_updated: 2026-02-19T08:18:24Z
day: '30'
ddc:
- '000'
department:
- _id: MaMo
external_id:
pmid:
- '41321376'
file:
- access_level: open_access
checksum: f774f8619a0d72f3975d9cb23942a1e9
content_type: application/pdf
creator: dernst
date_created: 2026-02-19T08:15:48Z
date_updated: 2026-02-19T08:15:48Z
file_id: '21336'
file_name: 2025_ICML_Gozeten.pdf
file_size: 471176
relation: main_file
success: 1
file_date_updated: 2026-02-19T08:15:48Z
has_accepted_license: '1'
intvolume: ' 267'
language:
- iso: eng
month: '11'
oa: 1
oa_version: Published Version
page: 20266-20295
pmid: 1
project:
- _id: 911e6d1f-16d5-11f0-9cad-c5c68c6a1cdf
grant_number: '101161364'
name: 'Inference in High Dimensions: Light-speed Algorithms and Information Limits'
publication: Proceedings of the 42nd International Conference on Machine Learning
publication_identifier:
eissn:
- 2640-3498
publication_status: published
publisher: ML Research Press
quality_controlled: '1'
status: public
title: Test-time training provably improves transformers as in-context learners
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: 267
year: '2025'
...
---
OA_place: publisher
OA_type: gold
_id: '21327'
abstract:
- lang: eng
text: Proteins exist as a dynamic ensemble of multiple conformations, and these
motions are often crucial for their functions. However, current structure prediction
methods predominantly yield a single conformation, overlooking the conformational
heterogeneity revealed by diverse experimental modalities. Here, we present a
framework for building experiment-grounded protein structure generative models
that infer conformational ensembles consistent with measured experimental data.
The key idea is to treat stateof-the-art protein structure predictors (e.g., AlphaFold3)
as sequence-conditioned structural priors, and cast ensemble modeling as posterior
inference of protein structures given experimental measurements. Through extensive
real-data experiments, we demonstrate the generality of our method to incorporate
a variety of experimental measurements. In particular, our framework uncovers
previously unmodeled conformational heterogeneity from crystallographic densities,
and generates high-accuracy NMR ensembles orders of magnitude faster than the
status quo. Notably, we demonstrate that our ensembles outperform AlphaFold3 (Abramson
et al., 2024) and sometimes better fit experimental data than publicly deposited
structures to the Protein Data Bank (PDB, Burley et al. (2017)). We believe that
this approach will unlock building predictive models that fully embrace experimentally
observed conformational diversity.
acknowledged_ssus:
- _id: ScienComp
acknowledgement: 'This work was supported by the Israeli Science Foundation (ISF)
grant number 1834/24. We acknowledge support from the Austrian Science Fund (FWF,
grant numbers I5812-B and I6223) and the financial support of the Helmsley Fellowships
Program for Sustainability and Health. This research uses resources of the Institute
of Science and Technology Austria’s scientific computing cluster. '
alternative_title:
- PMLR
article_processing_charge: No
arxiv: 1
author:
- first_name: Sai A
full_name: Maddipatla, Sai A
id: e957f5e5-91c9-11f0-a95f-e090f66ecb4d
last_name: Maddipatla
- first_name: Nadav E
full_name: Sellam, Nadav E
id: ef280fe0-91c9-11f0-a95f-8dea3f5bc513
last_name: Sellam
- first_name: Meital I
full_name: Bojan, Meital I
id: 11d88cf5-91ca-11f0-a95f-edf9f08f47b7
last_name: Bojan
- first_name: Sanketh
full_name: Vedula, Sanketh
id: 94f2fe44-70fa-11f0-b76b-92922c09452b
last_name: Vedula
- first_name: Paul
full_name: Schanda, Paul
id: 7B541462-FAF6-11E9-A490-E8DFE5697425
last_name: Schanda
orcid: 0000-0002-9350-7606
- first_name: Ailie
full_name: Marx, Ailie
last_name: Marx
- first_name: Alexander
full_name: Bronstein, Alexander
id: 58f3726e-7cba-11ef-ad8b-e6e8cb3904e6
last_name: Bronstein
orcid: 0000-0001-9699-8730
citation:
ama: 'Maddipatla SA, Sellam NE, Bojan MI, et al. Inverse problems with experiment-guided
AlphaFold. In: Proceedings of the 42nd International Conference on Machine
Learning. Vol 267. ML Research Press; 2025:42366-42393.'
apa: 'Maddipatla, S. A., Sellam, N. E., Bojan, M. I., Vedula, S., Schanda, P., Marx,
A., & Bronstein, A. M. (2025). Inverse problems with experiment-guided AlphaFold.
In Proceedings of the 42nd International Conference on Machine Learning
(Vol. 267, pp. 42366–42393). Vancouver, Canada: ML Research Press.'
chicago: Maddipatla, Sai A, Nadav E Sellam, Meital I Bojan, Sanketh Vedula, Paul
Schanda, Ailie Marx, and Alex M. Bronstein. “Inverse Problems with Experiment-Guided
AlphaFold.” In Proceedings of the 42nd International Conference on Machine
Learning, 267:42366–93. ML Research Press, 2025.
ieee: S. A. Maddipatla et al., “Inverse problems with experiment-guided AlphaFold,”
in Proceedings of the 42nd International Conference on Machine Learning,
Vancouver, Canada, 2025, vol. 267, pp. 42366–42393.
ista: 'Maddipatla SA, Sellam NE, Bojan MI, Vedula S, Schanda P, Marx A, Bronstein
AM. 2025. Inverse problems with experiment-guided AlphaFold. Proceedings of the
42nd International Conference on Machine Learning. ICML: International Conference
on Machine Learning, PMLR, vol. 267, 42366–42393.'
mla: Maddipatla, Sai A., et al. “Inverse Problems with Experiment-Guided AlphaFold.”
Proceedings of the 42nd International Conference on Machine Learning, vol.
267, ML Research Press, 2025, pp. 42366–93.
short: S.A. Maddipatla, N.E. Sellam, M.I. Bojan, S. Vedula, P. Schanda, A. Marx,
A.M. Bronstein, in:, Proceedings of the 42nd International Conference on Machine
Learning, ML Research Press, 2025, pp. 42366–42393.
conference:
end_date: 2025-07-19
location: Vancouver, Canada
name: 'ICML: International Conference on Machine Learning'
start_date: 2025-07-13
corr_author: '1'
date_created: 2026-02-18T12:11:17Z
date_published: 2025-07-30T00:00:00Z
date_updated: 2026-02-19T08:56:43Z
day: '30'
ddc:
- '000'
- '540'
department:
- _id: PaSc
- _id: AlBr
- _id: GradSch
external_id:
arxiv:
- '2502.09372'
file:
- access_level: open_access
checksum: f33230a6d59b7978d4cd72795e4e9059
content_type: application/pdf
creator: dernst
date_created: 2026-02-19T08:56:10Z
date_updated: 2026-02-19T08:56:10Z
file_id: '21338'
file_name: 2025_ICML_Maddipatla.pdf
file_size: 1924177
relation: main_file
success: 1
file_date_updated: 2026-02-19T08:56:10Z
has_accepted_license: '1'
intvolume: ' 267'
language:
- iso: eng
month: '07'
oa: 1
oa_version: Published Version
page: 42366 - 42393
project:
- _id: eb9c82eb-77a9-11ec-83b8-aadd536561cf
grant_number: I05812
name: AlloSpace. The emergence and mechanisms of allostery
- _id: bdb9578d-d553-11ed-ba76-ed5d39fce6f0
grant_number: I06223
name: Structure and mechanism of the mitochondrial MIM insertase
publication: Proceedings of the 42nd International Conference on Machine Learning
publication_identifier:
eissn:
- 2640-3498
publication_status: published
publisher: ML Research Press
quality_controlled: '1'
status: public
title: Inverse problems with experiment-guided AlphaFold
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: 267
year: '2025'
...
---
OA_place: publisher
OA_type: gold
_id: '21328'
abstract:
- lang: eng
text: Multi-index models provide a popular framework to investigate the learnability
of functions with low-dimensional structure and, also due to their connections
with neural networks, they have been object of recent intensive study. In this
paper, we focus on recovering the subspace spanned by the signals via spectral
estimators – a family of methods routinely used in practice, often as a warm-start
for iterative algorithms. Our main technical contribution is a precise asymptotic
characterization of the performance of spectral methods, when sample size and
input dimension grow proportionally and the dimension p of the space to recover
is fixed. Specifically, we locate the top-p eigenvalues of the spectral matrix
and establish the overlaps between the corresponding eigenvectors (which give
the spectral estimators) and a basis of the signal subspace. Our analysis unveils
a phase transition phenomenon in which, as the sample complexity grows, eigenvalues
escape from the bulk of the spectrum and, when that happens, eigenvectors recover
directions of the desired subspace. The precise characterization we put forward
enables the optimization of the data preprocessing, thus allowing to identify
the spectral estimator that requires the minimal sample size for weak recovery.
acknowledgement: "This work was done when Y. Z. was at the Institute of Science and
Technology Austria. Y. Z. and\r\nM. M. are funded by the European Union (ERC, INF2,
project number 101161364). Views and\r\nopinions expressed are however those of
the author(s) only and do not necessarily reflect those of the European Union or
the European Research Council Executive Agency. Neither the European Union nor the
granting authority can be held responsible for them. The authors would like to acknowledge
(in alphabetical order) discussions with Yatin Dandi, Leonardo Defilippis and Bruno
Loureiro concerning their parallel work (Defilippis et al., 2025)."
alternative_title:
- PMLR
article_processing_charge: No
arxiv: 1
author:
- first_name: Filip
full_name: Kovačević, Filip
id: d0258e7b-50b8-11ef-ad56-8b9f537b6b1b
last_name: Kovačević
- first_name: Zhang
full_name: Yihan, Zhang
last_name: Yihan
- first_name: Marco
full_name: Mondelli, Marco
id: 27EB676C-8706-11E9-9510-7717E6697425
last_name: Mondelli
orcid: 0000-0002-3242-7020
citation:
ama: 'Kovačević F, Yihan Z, Mondelli M. Spectral estimators for multi-index models:
Precise asymptotics and optimal weak recovery. In: Proceedings of 38th Conference
on Learning Theory. Vol 291. ML Research Press; 2025:3354-3404.'
apa: 'Kovačević, F., Yihan, Z., & Mondelli, M. (2025). Spectral estimators for
multi-index models: Precise asymptotics and optimal weak recovery. In Proceedings
of 38th Conference on Learning Theory (Vol. 291, pp. 3354–3404). Lyon, France:
ML Research Press.'
chicago: 'Kovačević, Filip, Zhang Yihan, and Marco Mondelli. “Spectral Estimators
for Multi-Index Models: Precise Asymptotics and Optimal Weak Recovery.” In Proceedings
of 38th Conference on Learning Theory, 291:3354–3404. ML Research Press, 2025.'
ieee: 'F. Kovačević, Z. Yihan, and M. Mondelli, “Spectral estimators for multi-index
models: Precise asymptotics and optimal weak recovery,” in Proceedings of 38th
Conference on Learning Theory, Lyon, France, 2025, vol. 291, pp. 3354–3404.'
ista: 'Kovačević F, Yihan Z, Mondelli M. 2025. Spectral estimators for multi-index
models: Precise asymptotics and optimal weak recovery. Proceedings of 38th Conference
on Learning Theory. COLT: Conference on Learning Theory, PMLR, vol. 291, 3354–3404.'
mla: 'Kovačević, Filip, et al. “Spectral Estimators for Multi-Index Models: Precise
Asymptotics and Optimal Weak Recovery.” Proceedings of 38th Conference on Learning
Theory, vol. 291, ML Research Press, 2025, pp. 3354–404.'
short: F. Kovačević, Z. Yihan, M. Mondelli, in:, Proceedings of 38th Conference
on Learning Theory, ML Research Press, 2025, pp. 3354–3404.
conference:
end_date: 2025-07-04
location: Lyon, France
name: 'COLT: Conference on Learning Theory'
start_date: 2025-06-30
corr_author: '1'
date_created: 2026-02-18T12:12:47Z
date_published: 2025-07-01T00:00:00Z
date_updated: 2026-02-19T09:03:53Z
day: '01'
ddc:
- '000'
department:
- _id: MaMo
external_id:
arxiv:
- '2502.01583'
file:
- access_level: open_access
checksum: 19aa70ab4f57fb9067b6ebb99a5fd6f0
content_type: application/pdf
creator: dernst
date_created: 2026-02-19T09:03:43Z
date_updated: 2026-02-19T09:03:43Z
file_id: '21339'
file_name: 2025_LearningTheory_Kovacevic.pdf
file_size: 844611
relation: main_file
success: 1
file_date_updated: 2026-02-19T09:03:43Z
has_accepted_license: '1'
intvolume: ' 291'
language:
- iso: eng
month: '07'
oa: 1
oa_version: Published Version
page: 3354-3404
project:
- _id: 911e6d1f-16d5-11f0-9cad-c5c68c6a1cdf
grant_number: '101161364'
name: 'Inference in High Dimensions: Light-speed Algorithms and Information Limits'
publication: Proceedings of 38th Conference on Learning Theory
publication_identifier:
eissn:
- 2640-3498
publication_status: published
publisher: ML Research Press
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'Spectral estimators for multi-index models: Precise asymptotics and optimal
weak recovery'
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: 291
year: '2025'
...
---
DOAJ_listed: '1'
OA_place: publisher
OA_type: gold
PlanS_conform: '1'
_id: '21413'
abstract:
- lang: eng
text: "We present a general framework for applying learning algorithms and heuristical
guidance to the verification of Markov decision processes (MDPs).\r\nThe primary
goal of our techniques is to improve performance by avoiding an exhaustive exploration
of the state space, instead focussing on particularly relevant areas of the system,
guided by heuristics. Our work builds on the previous results of Br{á}zdil et
al., significantly extending it as well as refining several details and fixing
errors.\r\nThe presented framework focuses on probabilistic reachability, which
is a core problem in verification, and is instantiated in two distinct scenarios.\r\nThe
first assumes that full knowledge of the MDP is available, in particular precise
transition probabilities. It performs a heuristic-driven partial exploration of
the model, yielding precise lower and upper bounds on the required probability.
The second tackles the case where we may only sample the MDP without knowing the
exact transition dynamics. Here, we obtain probabilistic guarantees, again in
terms of both the lower and upper bounds, which provides efficient stopping criteria
for the approximation. In particular, the latter is an extension of statistical
model-checking (SMC) for unbounded properties in MDPs. In contrast to other related
approaches, we do not restrict our attention to time-bounded (finite-horizon)
or discounted properties, nor assume any particular structural properties of the
MDP."
acknowledgement: "This research was funded in part by the European Research Council
(ERC) under grant agreement AdG-267989 (QUAREM)*, AdG-246967 (VERIWARE)*, StG-279307
(Graph Games)*\r\n, CoG-863818 (ForM-SMArt), and AdG-834115 (FUN2MODEL), by the
EU FP7 project HIERATIC*, by the German Research Foundation (DFG) project 427755713
(GOPro), by the Austrian Science Fund (FWF) projects S11402-N23 (RiSE)* , S11407-N23
(RiSE)*\r\n, and P23499-N23* , by the Czech Science Foundation grant No P202/12/P612*
and GA23-06963S, by the MUNI Award in Science and Humanities (MUNI/I/1757/2021)
of the Grant\r\nAgency of Masaryk University, by EPSRC project EP/K038575/1*, and
by the Microsoft faculty fellows award*. A preliminary version of this article appeared
at ATVA 2014 [33]. The * indicates funding that supported that version."
article_number: '10'
article_processing_charge: Yes
article_type: original
arxiv: 1
author:
- first_name: Tomáš
full_name: Brázdil, Tomáš
last_name: Brázdil
- first_name: Krishnendu
full_name: Chatterjee, Krishnendu
id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
last_name: Chatterjee
orcid: 0000-0002-4561-241X
- first_name: Martin
full_name: Chmelik, Martin
id: 3624234E-F248-11E8-B48F-1D18A9856A87
last_name: Chmelik
- first_name: Vojtěch
full_name: Forejt, Vojtěch
last_name: Forejt
- first_name: Jan
full_name: Kretinsky, Jan
id: 44CEF464-F248-11E8-B48F-1D18A9856A87
last_name: Kretinsky
orcid: 0000-0002-8122-2881
- first_name: Marta
full_name: Kwiatkowska, Marta
last_name: Kwiatkowska
- first_name: Tobias
full_name: Meggendorfer, Tobias
id: b21b0c15-30a2-11eb-80dc-f13ca25802e1
last_name: Meggendorfer
orcid: 0000-0002-1712-2165
- first_name: David
full_name: Parker, David
last_name: Parker
- first_name: Mateusz
full_name: Ujma, Mateusz
last_name: Ujma
citation:
ama: Brázdil T, Chatterjee K, Chmelik M, et al. Learning algorithms for verification
of Markov decision processes. TheoretiCS. 2025;4. doi:10.46298/theoretics.25.10
apa: Brázdil, T., Chatterjee, K., Chmelik, M., Forejt, V., Kretinsky, J., Kwiatkowska,
M., … Ujma, M. (2025). Learning algorithms for verification of Markov decision
processes. TheoretiCS. TheoretiCS Foundation. https://doi.org/10.46298/theoretics.25.10
chicago: Brázdil, Tomáš, Krishnendu Chatterjee, Martin Chmelik, Vojtěch Forejt,
Jan Kretinsky, Marta Kwiatkowska, Tobias Meggendorfer, David Parker, and Mateusz
Ujma. “Learning Algorithms for Verification of Markov Decision Processes.” TheoretiCS.
TheoretiCS Foundation, 2025. https://doi.org/10.46298/theoretics.25.10.
ieee: T. Brázdil et al., “Learning algorithms for verification of Markov
decision processes,” TheoretiCS, vol. 4. TheoretiCS Foundation, 2025.
ista: Brázdil T, Chatterjee K, Chmelik M, Forejt V, Kretinsky J, Kwiatkowska M,
Meggendorfer T, Parker D, Ujma M. 2025. Learning algorithms for verification of
Markov decision processes. TheoretiCS. 4, 10.
mla: Brázdil, Tomáš, et al. “Learning Algorithms for Verification of Markov Decision
Processes.” TheoretiCS, vol. 4, 10, TheoretiCS Foundation, 2025, doi:10.46298/theoretics.25.10.
short: T. Brázdil, K. Chatterjee, M. Chmelik, V. Forejt, J. Kretinsky, M. Kwiatkowska,
T. Meggendorfer, D. Parker, M. Ujma, TheoretiCS 4 (2025).
date_created: 2026-03-08T23:01:46Z
date_published: 2025-04-01T00:00:00Z
date_updated: 2026-03-09T11:43:38Z
day: '01'
ddc:
- '000'
department:
- _id: KrCh
doi: 10.46298/theoretics.25.10
ec_funded: 1
external_id:
arxiv:
- '2403.09184'
file:
- access_level: open_access
checksum: 2ccf563ae577ee08d82baf752292ca7b
content_type: application/pdf
creator: dernst
date_created: 2026-03-09T11:39:59Z
date_updated: 2026-03-09T11:39:59Z
file_id: '21417'
file_name: 2026_TheoretiCS_Brazdil.pdf
file_size: 861607
relation: main_file
success: 1
file_date_updated: 2026-03-09T11:39:59Z
fulldoi: https://doi.org/10.46298/theoretics.25.10
has_accepted_license: '1'
intvolume: ' 4'
language:
- iso: eng
month: '04'
oa: 1
oa_version: Published Version
project:
- _id: 25EE3708-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '267989'
name: Quantitative Reactive Modeling
- _id: 2581B60A-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '279307'
name: 'Quantitative Graph Games: Theory and Applications'
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
- _id: 25F2ACDE-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: S11402-N23
name: Rigorous Systems Engineering
- _id: 2584A770-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P 23499-N23
name: Modern Graph Algorithmic Techniques in Formal Verification
publication: TheoretiCS
publication_identifier:
eissn:
- 2751-4838
publication_status: published
publisher: TheoretiCS Foundation
quality_controlled: '1'
scopus_import: '1'
status: public
title: Learning algorithms for verification of Markov decision processes
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 4
year: '2025'
...
---
OA_place: repository
OA_type: green
_id: '21435'
abstract:
- lang: eng
text: Multiferroic materials, in which electric polarization and magnetic order
coexist and couple, offer rich opportunities for both fundamental discovery and
technology. However, multiferroicity remains rare due to conflicting electronic
requirements for ferroelectricity and magnetism. One route to circumvent this
challenge is to exploit the noncollinear ordering of spin cycloids, whose symmetry
permits the emergence of polar order. In this work, we introduce another pathway
to multiferroic order in which strain generates polarization in materials that
host nonpolar spin spirals. To demonstrate this phenomenon, we chose the spin
spiral in the well-studied helimagnet Cr1/3NbS2. To detect the induced polarization,
we introduce the technique of magnetoelectric birefringence (MEB), an optical
probe that enables spatially-resolved and unambiguous detection of polar order.
By combining MEB imaging with strain engineering, we confirm the onset of a polar
vector at the magnetic transition, establishing strained Cr1/3NbS2 as a type-II
multiferroic.
acknowledgement: "Y.S., V.S. and J.O. received support from the Gordon and Betty Moore
Foundation’s\r\nEPiQS Initiative through Grant GBMF4537 to J.O. at UC Berkeley.
Experimental and theoretical work at LBNL and UC Berkeley was funded by the Quantum
Materials (KC2202) program under the U.S. Department of Energy, Office of Science,
Office of Basic Energy Sciences,\r\nMaterials Sciences and Engineering Division
under Contract No. DE-AC02-05CH11231.\r\nY.S. also acknowledges support by the David
J. Thouless Postdoctoral Fellowship at the\r\nDepartment of Physics, University
of Washington. DGM acknowledges support from the\r\nGordon and Betty Moore Foundation’s
EPiQS Initiative, Grant GBMF9069. L.Z. acknowledges the support from the U.S. Department
of Energy (DOE), Office of Science, Basic\r\nEnergy Science (BES), under award No.
DE-SC0024145"
article_number: '2510.11619'
article_processing_charge: No
arxiv: 1
author:
- first_name: Y.
full_name: Sun, Y.
last_name: Sun
- first_name: Y.
full_name: Ahn, Y.
last_name: Ahn
- first_name: D.
full_name: Sapkota, D.
last_name: Sapkota
- first_name: H. S.
full_name: Arachchige, H. S.
last_name: Arachchige
- first_name: R.
full_name: Xue, R.
last_name: Xue
- first_name: S.
full_name: Mozaffari, S.
last_name: Mozaffari
- first_name: D. G.
full_name: Mandrus, D. G.
last_name: Mandrus
- first_name: L.
full_name: Zhao, L.
last_name: Zhao
- first_name: J.
full_name: Orenstein, J.
last_name: Orenstein
- first_name: Veronika
full_name: Sunko, Veronika
id: 23cb1cf6-2c7a-11ef-91a4-f72fc19f20b3
last_name: Sunko
orcid: 0000-0003-2724-3523
citation:
ama: Sun Y, Ahn Y, Sapkota D, et al. Strain-induced multiferroicity in Cr1/3NbS2.
arXiv. doi:10.48550/arXiv.2510.11619
apa: Sun, Y., Ahn, Y., Sapkota, D., Arachchige, H. S., Xue, R., Mozaffari, S., …
Sunko, V. (n.d.). Strain-induced multiferroicity in Cr1/3NbS2. arXiv. https://doi.org/10.48550/arXiv.2510.11619
chicago: Sun, Y., Y. Ahn, D. Sapkota, H. S. Arachchige, R. Xue, S. Mozaffari, D.
G. Mandrus, L. Zhao, J. Orenstein, and Veronika Sunko. “Strain-Induced Multiferroicity
in Cr1/3NbS2.” ArXiv, n.d. https://doi.org/10.48550/arXiv.2510.11619.
ieee: Y. Sun et al., “Strain-induced multiferroicity in Cr1/3NbS2,” arXiv.
.
ista: Sun Y, Ahn Y, Sapkota D, Arachchige HS, Xue R, Mozaffari S, Mandrus DG, Zhao
L, Orenstein J, Sunko V. Strain-induced multiferroicity in Cr1/3NbS2. arXiv, 2510.11619.
mla: Sun, Y., et al. “Strain-Induced Multiferroicity in Cr1/3NbS2.” ArXiv,
2510.11619, doi:10.48550/arXiv.2510.11619.
short: Y. Sun, Y. Ahn, D. Sapkota, H.S. Arachchige, R. Xue, S. Mozaffari, D.G. Mandrus,
L. Zhao, J. Orenstein, V. Sunko, ArXiv (n.d.).
corr_author: '1'
date_created: 2026-03-11T10:39:44Z
date_published: 2025-10-13T00:00:00Z
date_updated: 2026-03-16T08:43:57Z
day: '13'
department:
- _id: VeSu
doi: 10.48550/arXiv.2510.11619
external_id:
arxiv:
- '2510.11619'
fulldoi: https://doi.org/10.48550/arXiv.2510.11619
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2510.11619
month: '10'
oa: 1
oa_version: Preprint
publication: arXiv
publication_status: submitted
status: public
title: Strain-induced multiferroicity in Cr1/3NbS2
type: preprint
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2025'
...
---
OA_place: publisher
OA_type: gold
_id: '21474'
abstract:
- lang: eng
text: Rendering novel, relit views of a human head, given a monocular portrait image
as input, is an inherently underconstrained problem. The traditional graphics
solution is to explicitly decompose the input image into geometry, material and
lighting via differentiable rendering; but this is constrained by the multiple
assumptions and approximations of the underlying models and parameterizations
of these scene components. We propose 3DPR, an image-based relighting model that
leverages generative priors learnt from multi-view One-Light-at-A-Time (OLAT)
images captured in a light stage. We introduce a new diverse and large-scale multi-view
4K OLAT dataset of 139 subjects to learn a high-quality prior over the distribution
of high-frequency face reflectance. We leverage the latent space of a pre-trained
generative head model that provides a rich prior over face geometry learnt from
in-the-wild image datasets. The input portrait is first embedded in the latent
manifold of such a model through an encoder-based inversion process. Then a novel
triplane-based reflectance network trained on our lightstage data is used to synthesize
high-fidelity OLAT images to enable image-based relighting. Our reflectance network
operates in the latent space of the generative head model, crucially enabling
a relatively small number of lightstage images to train the reflectance model.
Combining the generated OLATs according to a given HDRI environment maps yields
physically accurate environmental relighting results. Through quantitative and
qualitative evaluations, we demonstrate that 3DPR outperforms previous methods,
particularly in preserving identity and in capturing lighting effects such as
specularities, self-shadows, and subsurface scattering.
acknowledgement: This work was supported by the ERC Consolidator Grant 4DReply (770784)
and Saarbrücken Research Center for Visual Comput- ing, Interaction, and AI. We
thank Oleksandr Sotnychenko for helping us with setting up data capture. Finally,
we thank Shrisha Bharadwaj for discussions, proofreading and innumerable support.
article_number: '108'
article_processing_charge: No
arxiv: 1
author:
- first_name: Pramod
full_name: Rao, Pramod
last_name: Rao
- first_name: Abhimitra
full_name: Meka, Abhimitra
last_name: Meka
- first_name: Xilong
full_name: Zhou, Xilong
last_name: Zhou
- first_name: Gereon
full_name: Fox, Gereon
last_name: Fox
- first_name: B. R.
full_name: Mallikarjun, B. R.
last_name: Mallikarjun
- first_name: Fangneng
full_name: Zhan, Fangneng
last_name: Zhan
- first_name: Tim
full_name: Weyrich, Tim
last_name: Weyrich
- first_name: Bernd
full_name: Bickel, Bernd
id: 49876194-F248-11E8-B48F-1D18A9856A87
last_name: Bickel
orcid: 0000-0001-6511-9385
- first_name: Hanspeter
full_name: Pfister, Hanspeter
last_name: Pfister
- first_name: Wojciech
full_name: Matusik, Wojciech
last_name: Matusik
- first_name: Thabo
full_name: Beeler, Thabo
last_name: Beeler
- first_name: Mohamed
full_name: Elgharib, Mohamed
last_name: Elgharib
- first_name: Marc
full_name: Habermann, Marc
last_name: Habermann
- first_name: Christian
full_name: Theobalt, Christian
last_name: Theobalt
citation:
ama: 'Rao P, Meka A, Zhou X, et al. 3DPR: Single image 3D portrait relighting with
generative priors. In: Proceedings SIGGRAPH Asia 2025 Conference Papers 2025.
Association for Computing Machinery; 2025. doi:10.1145/3757377.3763962'
apa: 'Rao, P., Meka, A., Zhou, X., Fox, G., Mallikarjun, B. R., Zhan, F., … Theobalt,
C. (2025). 3DPR: Single image 3D portrait relighting with generative priors. In
Proceedings SIGGRAPH Asia 2025 Conference Papers 2025. Hong Kong, Hong
Kong: Association for Computing Machinery. https://doi.org/10.1145/3757377.3763962'
chicago: 'Rao, Pramod, Abhimitra Meka, Xilong Zhou, Gereon Fox, B. R. Mallikarjun,
Fangneng Zhan, Tim Weyrich, et al. “3DPR: Single Image 3D Portrait Relighting
with Generative Priors.” In Proceedings SIGGRAPH Asia 2025 Conference Papers
2025. Association for Computing Machinery, 2025. https://doi.org/10.1145/3757377.3763962.'
ieee: 'P. Rao et al., “3DPR: Single image 3D portrait relighting with generative
priors,” in Proceedings SIGGRAPH Asia 2025 Conference Papers 2025, Hong
Kong, Hong Kong, 2025.'
ista: 'Rao P, Meka A, Zhou X, Fox G, Mallikarjun BR, Zhan F, Weyrich T, Bickel B,
Pfister H, Matusik W, Beeler T, Elgharib M, Habermann M, Theobalt C. 2025. 3DPR:
Single image 3D portrait relighting with generative priors. Proceedings SIGGRAPH
Asia 2025 Conference Papers 2025. SA: SIGGRAPH Asia, 108.'
mla: 'Rao, Pramod, et al. “3DPR: Single Image 3D Portrait Relighting with Generative
Priors.” Proceedings SIGGRAPH Asia 2025 Conference Papers 2025, 108, Association
for Computing Machinery, 2025, doi:10.1145/3757377.3763962.'
short: P. Rao, A. Meka, X. Zhou, G. Fox, B.R. Mallikarjun, F. Zhan, T. Weyrich,
B. Bickel, H. Pfister, W. Matusik, T. Beeler, M. Elgharib, M. Habermann, C. Theobalt,
in:, Proceedings SIGGRAPH Asia 2025 Conference Papers 2025, Association for Computing
Machinery, 2025.
conference:
end_date: 2025-12-18
location: Hong Kong, Hong Kong
name: 'SA: SIGGRAPH Asia'
start_date: 2025-12-15
date_created: 2026-03-22T23:04:35Z
date_published: 2025-12-14T00:00:00Z
date_updated: 2026-03-23T14:45:58Z
day: '14'
ddc:
- '000'
department:
- _id: BeBi
doi: 10.1145/3757377.3763962
external_id:
arxiv:
- '2510.15846'
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creator: dernst
date_created: 2026-03-23T14:41:07Z
date_updated: 2026-03-23T14:41:07Z
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language:
- iso: eng
license: https://creativecommons.org/licenses/by-nc/4.0/
month: '12'
oa: 1
oa_version: Published Version
publication: Proceedings SIGGRAPH Asia 2025 Conference Papers 2025
publication_identifier:
isbn:
- '9798400721373'
publication_status: published
publisher: Association for Computing Machinery
quality_controlled: '1'
scopus_import: '1'
status: public
title: '3DPR: Single image 3D portrait relighting with generative priors'
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type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2025'
...
---
OA_place: repository
OA_type: gold
_id: '21668'
abstract:
- lang: eng
text: "This artifact allows to review and reproduce the experiments from the paper
*A Revised Practitioner's Guide to MDP Model Checking Algorithms*.\r\nThe package
contains all original logfiles and derived data used to generate the plots as
in the paper. Furthermore, the artifact contains the model checking tools `Storm`
and `mcsta` in the version exercised in the paper, the used Docker container,
as well as benchmark instances and execution scripts to reproduce the experiments.\r\n\r\nSee
also the artifact of the conference paper: https://zenodo.org/records/7509474"
article_processing_charge: No
author:
- first_name: Arnd
full_name: Hartmanns, Arnd
last_name: Hartmanns
- first_name: Sebastian
full_name: Junges, Sebastian
last_name: Junges
- first_name: Tim
full_name: Quatmann, Tim
last_name: Quatmann
- first_name: Maximilian
full_name: Weininger, Maximilian
id: 02ab0197-cc70-11ed-ab61-918e71f56881
last_name: Weininger
orcid: 0000-0002-0163-2152
citation:
ama: Hartmanns A, Junges S, Quatmann T, Weininger M. Benchmark data for the revised
practitioner’s guide to MDP model checking algorithms. 2025. doi:10.5281/ZENODO.14500423
apa: Hartmanns, A., Junges, S., Quatmann, T., & Weininger, M. (2025). Benchmark
data for the revised practitioner’s guide to MDP model checking algorithms. Zenodo.
https://doi.org/10.5281/ZENODO.14500423
chicago: Hartmanns, Arnd, Sebastian Junges, Tim Quatmann, and Maximilian Weininger.
“Benchmark Data for the Revised Practitioner’s Guide to MDP Model Checking Algorithms.”
Zenodo, 2025. https://doi.org/10.5281/ZENODO.14500423.
ieee: A. Hartmanns, S. Junges, T. Quatmann, and M. Weininger, “Benchmark data for
the revised practitioner’s guide to MDP model checking algorithms.” Zenodo, 2025.
ista: Hartmanns A, Junges S, Quatmann T, Weininger M. 2025. Benchmark data for the
revised practitioner’s guide to MDP model checking algorithms, Zenodo, 10.5281/ZENODO.14500423.
mla: Hartmanns, Arnd, et al. Benchmark Data for the Revised Practitioner’s Guide
to MDP Model Checking Algorithms. Zenodo, 2025, doi:10.5281/ZENODO.14500423.
short: A. Hartmanns, S. Junges, T. Quatmann, M. Weininger, (2025).
date_created: 2026-04-07T09:47:22Z
date_published: 2025-03-07T00:00:00Z
date_updated: 2026-04-07T09:52:55Z
day: '07'
ddc:
- '000'
department:
- _id: KrCh
doi: 10.5281/ZENODO.14500423
fulldoi: https://doi.org/10.5281/ZENODO.14500423
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url: https://doi.org/10.5281/ZENODO.14500423
month: '03'
oa: 1
oa_version: Published Version
publisher: Zenodo
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status: public
title: Benchmark data for the revised practitioner's guide to MDP model checking algorithms
type: research_data_reference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2025'
...
---
OA_place: publisher
OA_type: hybrid
PlanS_conform: '1'
_id: '21706'
abstract:
- lang: eng
text: "Consider a quadratic polynomial Q(ξ1, . . . , ξn) of independent Rademacher
random variables ξ1, . . . , ξn. To what extent can Q(ξ1, . . . , ξn) concentrate
on a single value? This quadratic version of the classical Littlewood–Offord problem
was popularised by Costello, Tao and Vu in their study of symmetric random matrices.
In this paper, we obtain an essentially optimal bound for this problem, as conjectured
by Nguyen and Vu. Specifically, if Q(ξ1, . . . , ξn) ‘robustly depends on at least
m of the ξi’ in the sense that there is no way to pin down the value of Q(ξ1,
. . . , ξn) by fixing values for fewer than m of the variables ξi, then we have
Pr[Q(ξ1, . . . , ξn) = 0] ≤ O(1/√m). This also implies a similar result in the
case where ξ1, . . . , ξn have arbitrary distributions. Our proof combines a number
of ideas that may be of independent interest, including an inductive decoupling
scheme that reduces quadratic anticoncentration problems\r\nto high-dimensional
linear anticoncentration problems. Also, one application of our main result is
the resolution of a conjecture of Alon, Hefetz, Krivelevich and Tyomkyn related
to graph inducibility. "
acknowledgement: We would like to thank the anonymous referee for a number of helpful
comments and suggestions. Matthew Kwan was supported by ERC Starting Grant “RANDSTRUCT”
No. 101076777. Lisa Sauermann was supported in part by NSF Award DMS-2100157 and
a Sloan Research Fellowship, and in part by the DFG Heisenberg Program.
article_processing_charge: Yes (via OA deal)
article_type: original
arxiv: 1
author:
- first_name: Matthew Alan
full_name: Kwan, Matthew Alan
id: 5fca0887-a1db-11eb-95d1-ca9d5e0453b3
last_name: Kwan
orcid: 0000-0002-4003-7567
- first_name: Lisa
full_name: Sauermann, Lisa
last_name: Sauermann
citation:
ama: Kwan MA, Sauermann L. Resolution of the quadratic Littlewood–Offord problem.
Compositio Mathematica. 2025;161(12):3089-3139. doi:10.1112/S0010437X25102789
apa: Kwan, M. A., & Sauermann, L. (2025). Resolution of the quadratic Littlewood–Offord
problem. Compositio Mathematica. Cambridge University Press. https://doi.org/10.1112/S0010437X25102789
chicago: Kwan, Matthew Alan, and Lisa Sauermann. “Resolution of the Quadratic Littlewood–Offord
Problem.” Compositio Mathematica. Cambridge University Press, 2025. https://doi.org/10.1112/S0010437X25102789.
ieee: M. A. Kwan and L. Sauermann, “Resolution of the quadratic Littlewood–Offord
problem,” Compositio Mathematica, vol. 161, no. 12. Cambridge University
Press, pp. 3089–3139, 2025.
ista: Kwan MA, Sauermann L. 2025. Resolution of the quadratic Littlewood–Offord
problem. Compositio Mathematica. 161(12), 3089–3139.
mla: Kwan, Matthew Alan, and Lisa Sauermann. “Resolution of the Quadratic Littlewood–Offord
Problem.” Compositio Mathematica, vol. 161, no. 12, Cambridge University
Press, 2025, pp. 3089–139, doi:10.1112/S0010437X25102789.
short: M.A. Kwan, L. Sauermann, Compositio Mathematica 161 (2025) 3089–3139.
corr_author: '1'
date_created: 2026-04-12T22:01:48Z
date_published: 2025-12-01T00:00:00Z
date_updated: 2026-05-04T09:42:57Z
day: '01'
ddc:
- '510'
department:
- _id: MaKw
doi: 10.1112/S0010437X25102789
external_id:
arxiv:
- '2312.13826'
file:
- access_level: open_access
checksum: bd3415bb435da9d0b39f6f9a18c61abb
content_type: application/pdf
creator: dernst
date_created: 2026-05-04T09:41:25Z
date_updated: 2026-05-04T09:41:25Z
file_id: '21787'
file_name: 2025_CompositioMath_Kwan.pdf
file_size: 858727
relation: main_file
success: 1
file_date_updated: 2026-05-04T09:41:25Z
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issue: '12'
language:
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month: '12'
oa: 1
oa_version: Published Version
page: 3089-3139
project:
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grant_number: '101076777'
name: Randomness and structure in combinatorics
publication: Compositio Mathematica
publication_identifier:
eissn:
- 1570-5846
issn:
- 0010-437X
publication_status: published
publisher: Cambridge University Press
quality_controlled: '1'
scopus_import: '1'
status: public
title: Resolution of the quadratic Littlewood–Offord problem
tmp:
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type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 161
year: '2025'
...
---
DOAJ_listed: '1'
OA_place: publisher
OA_type: gold
PlanS_conform: '1'
_id: '21724'
abstract:
- lang: eng
text: 'The next generation of weak-gravitational-lensing surveys has the potential
to place stringent constraints on cosmological parameters. However, their analysis
is limited by systematics such as the intrinsic alignments of galaxies, which
alter weak-lensing convergence and can lead to biases in cosmological parameter
estimations. For the first time, in this work, we investigate the impact of intrinsic
alignments on non-Gaussian statistics of the weak-lensing field using galaxy shapes
derived from the IllustrisTNG hydrodynamical simulation. We create two catalogs
of ray-traced convergence maps: one that includes the measured intrinsic shape
of each galaxy and another where all galaxies are randomly rotated to eliminate
intrinsic alignments. We compare a range of weak-lensing statistics between the
two catalogs, including the shear–shear correlation function, the map-level angular
power spectrum, one-point, peak count, and minimum distribution functions, and
Minkowski functionals. For each statistic, we assess the level of statistical
distinguishability between catalogs for a set of future survey angular areas.
Our results reveal strong small-scale correlation in the alignment of galaxies
and statistically significant boosts in weak-lensing convergence in both positive
and negative directions for high-significance peaks and minima, respectively.
We note that our analysis is at a fixed number density of ˜ 5 arcmin^-2, drawn
from a single realization of initial conditions, and does not include observational
uncertainties or supersample covariance contributions. Weak-lensing analyses utilizing
non-Gaussian statistics must account for intrinsic alignments to avoid significantly
compromised cosmological inferences.'
acknowledgement: We thank Fulvio Ferlito, Ana Maria Delgado, and Ken Osato for helpful
conversations during this work. M.E.L. is supported by NSF grant DGE-2036197. Z.H.
acknowledges financial support from NASA ATP grant 80NSSC24K1093. The Flatiron Institute
is supported by the Simons Foundation.
article_number: '36'
article_processing_charge: Yes
article_type: original
arxiv: 1
author:
- first_name: Max E.
full_name: Lee, Max E.
last_name: Lee
- first_name: Zoltán
full_name: Haiman, Zoltán
id: 7c006e8c-cc0d-11ee-8322-cb904ef76f36
last_name: Haiman
orcid: 0000-0003-3633-5403
- first_name: Shivam
full_name: Pandey, Shivam
last_name: Pandey
- first_name: Shy
full_name: Genel, Shy
last_name: Genel
citation:
ama: Lee ME, Haiman Z, Pandey S, Genel S. The effect of intrinsic alignments on
weak-lensing statistics in hydrodynamical simulations. The Astrophysical Journal.
2025;996(1). doi:10.3847/1538-4357/ae1ca7
apa: Lee, M. E., Haiman, Z., Pandey, S., & Genel, S. (2025). The effect of intrinsic
alignments on weak-lensing statistics in hydrodynamical simulations. The Astrophysical
Journal. IOP Publishing. https://doi.org/10.3847/1538-4357/ae1ca7
chicago: Lee, Max E., Zoltán Haiman, Shivam Pandey, and Shy Genel. “The Effect of
Intrinsic Alignments on Weak-Lensing Statistics in Hydrodynamical Simulations.”
The Astrophysical Journal. IOP Publishing, 2025. https://doi.org/10.3847/1538-4357/ae1ca7.
ieee: M. E. Lee, Z. Haiman, S. Pandey, and S. Genel, “The effect of intrinsic alignments
on weak-lensing statistics in hydrodynamical simulations,” The Astrophysical
Journal, vol. 996, no. 1. IOP Publishing, 2025.
ista: Lee ME, Haiman Z, Pandey S, Genel S. 2025. The effect of intrinsic alignments
on weak-lensing statistics in hydrodynamical simulations. The Astrophysical Journal.
996(1), 36.
mla: Lee, Max E., et al. “The Effect of Intrinsic Alignments on Weak-Lensing Statistics
in Hydrodynamical Simulations.” The Astrophysical Journal, vol. 996, no.
1, 36, IOP Publishing, 2025, doi:10.3847/1538-4357/ae1ca7.
short: M.E. Lee, Z. Haiman, S. Pandey, S. Genel, The Astrophysical Journal 996 (2025).
date_created: 2026-04-12T22:01:52Z
date_published: 2025-12-23T00:00:00Z
date_updated: 2026-04-13T08:30:52Z
day: '23'
ddc:
- '520'
department:
- _id: ZoHa
doi: 10.3847/1538-4357/ae1ca7
external_id:
arxiv:
- '2504.12460'
file:
- access_level: open_access
checksum: 0d8fa05617420230eac39944b36839e9
content_type: application/pdf
creator: dernst
date_created: 2026-04-13T08:20:16Z
date_updated: 2026-04-13T08:20:16Z
file_id: '21732'
file_name: 2025_AstrophysicalJournal_Lee.pdf
file_size: 4122087
relation: main_file
success: 1
file_date_updated: 2026-04-13T08:20:16Z
fulldoi: https://doi.org/10.3847/1538-4357/ae1ca7
has_accepted_license: '1'
intvolume: ' 996'
issue: '1'
language:
- iso: eng
month: '12'
oa: 1
oa_version: Published Version
publication: The Astrophysical Journal
publication_identifier:
eissn:
- 1538-4357
issn:
- 0004-637X
publication_status: published
publisher: IOP Publishing
quality_controlled: '1'
scopus_import: '1'
status: public
title: The effect of intrinsic alignments on weak-lensing statistics in hydrodynamical
simulations
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user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
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...