--- OA_place: repository OA_type: green _id: '21207' abstract: - lang: eng text: Personalized federated learning has emerged as a popular approach to training on devices holding statistically heterogeneous data, known as clients. However, most existing approaches require a client to have labeled data for training or finetuning in order to obtain their own personalized model. In this paper we address this by proposing FLowDUP, a novel method that is able to generate a personalized model using only a forward pass with unlabeled data. The generated model parameters reside in a low-dimensional subspace, enabling efficient communication and computation. FLowDUP's learning objective is theoretically motivated by our new transductive multi-task PAC-Bayesian generalization bound, that provides performance guarantees for unlabeled clients. The objective is structured in such a way that it allows both clients with labeled data and clients with only unlabeled data to contribute to the training process. To supplement our theoretical results we carry out a thorough experimental evaluation of FLowDUP, demonstrating strong empirical performance on a range of datasets with differing sorts of statistically heterogeneous clients. Through numerous ablation studies, we test the efficacy of the individual components of the method. article_number: '2505.15579' article_processing_charge: No author: - first_name: Hossein full_name: Zakerinia, Hossein id: 653bd8b6-f394-11eb-9cf6-c0bbf6cd78d4 last_name: Zakerinia orcid: 0009-0007-3977-6462 - first_name: Jonathan A full_name: Scott, Jonathan A id: e499926b-f6e0-11ea-865d-9c63db0031e8 last_name: Scott - first_name: Christoph full_name: Lampert, Christoph id: 40C20FD2-F248-11E8-B48F-1D18A9856A87 last_name: Lampert orcid: 0000-0001-8622-7887 citation: ama: 'Zakerinia H, Scott JA, Lampert C. Federated learning with unlabeled clients: Personalization can happen in low dimensions. arXiv. doi:10.48550/ARXIV.2505.15579' apa: 'Zakerinia, H., Scott, J. A., & Lampert, C. (n.d.). Federated learning with unlabeled clients: Personalization can happen in low dimensions. arXiv. https://doi.org/10.48550/ARXIV.2505.15579' chicago: 'Zakerinia, Hossein, Jonathan A Scott, and Christoph Lampert. “Federated Learning with Unlabeled Clients: Personalization Can Happen in Low Dimensions.” ArXiv, n.d. https://doi.org/10.48550/ARXIV.2505.15579.' ieee: 'H. Zakerinia, J. A. Scott, and C. Lampert, “Federated learning with unlabeled clients: Personalization can happen in low dimensions,” arXiv. .' ista: 'Zakerinia H, Scott JA, Lampert C. Federated learning with unlabeled clients: Personalization can happen in low dimensions. arXiv, 2505.15579.' mla: 'Zakerinia, Hossein, et al. “Federated Learning with Unlabeled Clients: Personalization Can Happen in Low Dimensions.” ArXiv, 2505.15579, doi:10.48550/ARXIV.2505.15579.' short: H. Zakerinia, J.A. Scott, C. Lampert, ArXiv (n.d.). corr_author: '1' das_tickbox: '1' date_created: 2026-02-10T08:20:59Z date_published: 2025-05-21T00:00:00Z date_updated: 2026-07-22T06:34:28Z day: '21' department: - _id: ChLa doi: 10.48550/ARXIV.2505.15579 language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.48550/arXiv.2505.15579 month: '05' oa: 1 oa_version: Preprint publication: arXiv publication_status: draft related_material: record: - id: '21198' relation: dissertation_contains status: public status: public title: 'Federated learning with unlabeled clients: Personalization can happen in low dimensions' 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: preprint user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2025' ... --- OA_place: repository OA_type: green _id: '21050' abstract: - lang: eng text: "In 1873, James C. Maxwell conjectured that the electric field generated by $n$ point charges in generic position has at most $(n-1)^2$ isolated zeroes. The first (non-optimal) upper bound was only obtained in 2007 by Gabrielov, Novikov and Shapiro, who also posed two additional interesting conjectures.\r\n In this article, we give the best upper bound known to date on the number of zeroes of the electric field, and construct a counterexample to a conjecture of Gabrielov, Novikov and Shapiro that the number of equilibria cannot exceed those of the distance function defined by the unit point charges.\r\n Finally, we note that it is quite possible that Maxwell's quadratic upper bound is not tight, so it is prudent to find smaller bounds. Hence, we also explore examples and construct configurations of charges achieving the highest ratios of the number of electric field zeroes by point charges found to this day." article_number: '2501.05315' article_processing_charge: No arxiv: 1 author: - first_name: Herbert full_name: Edelsbrunner, Herbert id: 3FB178DA-F248-11E8-B48F-1D18A9856A87 last_name: Edelsbrunner orcid: 0000-0002-9823-6833 - first_name: Christopher D full_name: Fillmore, Christopher D id: 35638A5C-AAC7-11E9-B0BF-5503E6697425 last_name: Fillmore - first_name: Gonçalo full_name: Olivera, Gonçalo last_name: Olivera citation: ama: Edelsbrunner H, Fillmore CD, Olivera G. Counting equilibria of the electrostatic potential. arXiv. doi:10.48550/ARXIV.2501.05315 apa: Edelsbrunner, H., Fillmore, C. D., & Olivera, G. (n.d.). Counting equilibria of the electrostatic potential. arXiv. https://doi.org/10.48550/ARXIV.2501.05315 chicago: Edelsbrunner, Herbert, Christopher D Fillmore, and Gonçalo Olivera. “Counting Equilibria of the Electrostatic Potential.” ArXiv, n.d. https://doi.org/10.48550/ARXIV.2501.05315. ieee: H. Edelsbrunner, C. D. Fillmore, and G. Olivera, “Counting equilibria of the electrostatic potential,” arXiv. . ista: Edelsbrunner H, Fillmore CD, Olivera G. Counting equilibria of the electrostatic potential. arXiv, 2501.05315. mla: Edelsbrunner, Herbert, et al. “Counting Equilibria of the Electrostatic Potential.” ArXiv, 2501.05315, doi:10.48550/ARXIV.2501.05315. short: H. Edelsbrunner, C.D. Fillmore, G. Olivera, ArXiv (n.d.). corr_author: '1' das_tickbox: '1' date_created: 2026-01-27T14:29:27Z date_published: 2025-03-20T00:00:00Z date_updated: 2026-07-22T06:33:55Z day: '20' department: - _id: HeEd doi: 10.48550/ARXIV.2501.05315 external_id: arxiv: - '2501.05315' language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.48550/arXiv.2501.05315 month: '03' oa: 1 oa_version: Preprint publication: arXiv publication_status: draft related_material: record: - id: '21021' relation: dissertation_contains status: public - id: '21931' relation: later_version status: public status: public title: Counting equilibria of the electrostatic potential 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: preprint user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2025' ... --- OA_place: publisher OA_type: hybrid _id: '19025' abstract: - lang: eng text: 'A complete understanding of the central stars of planetary nebulae (CSPNe) remains elusive. Over the past several decades, time-series photometry of CSPNe has yielded significant results including, but not limited to, discoveries of nearly 100 binary systems, insights into pulsations and winds in young white dwarfs, and studies of stars undergoing very late thermal pulses. We have undertaken a systematic study of optical photometric variability of cataloged CSPNe, using the light curves from the Zwicky Transient Facility (ZTF). By applying appropriate variability metrics, we arrive at a list of 94 highly variable CSPN candidates. Based on the timescales of the light-curve activity, we classify the variables broadly into short- and long-timescale variables. In this first paper in this series, we focus on the former, which is the majority class comprising 83 objects. We report periods for six sources for the first time, and recover several known periodic variables. Among the aperiodic sources, most exhibit a jitter around a median flux with a stable amplitude, and a few show outbursts. We draw attention to WeSb 1, which shows a different kind of variability: prominent deep and aperiodic dips, resembling transits from a dust/debris disk. We find strong evidence for a binary nature of WeSb 1 (possibly an F-type subgiant companion). The compactness of the emission lines and inferred high electron densities make WeSb 1 a candidate for either an EGB 6-type planetary nucleus, or a symbiotic system inside an evolved planetary nebula, both of which are rare objects. To demonstrate further promise with ZTF, we report three additional newly identified periodic sources that do not appear in the list of highly variable sources. Finally, we also introduce a two-dimensional metric space defined by the von Neumann statistics and Pearson Skew and demonstrate its effectiveness in identifying unique variables of astrophysical interest, like WeSb 1.' acknowledgement: "This work is 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 Oskar Klein Center at Stockholm University, the University of Maryland, University of California, Berkeley, the University of Wisconsin at Milwaukee, University of Warwick, Ruhr University Bochum, Cornell University, Northwestern University, and Drexel University. Operations are conducted by COO, IPAC, and UW.\r\n\r\nThis 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.\r\n\r\nWe are grateful to the staffs of Palomar Observatory and the Hobby-Eberly Telescope for assistance with the observations and data management. The Liverpool Telescope is operated on the island of La Palma by Liverpool John Moores University in the Spanish Observatorio del Roque de los Muchachos of the Instituto de Astrofisica de Canarias with financial support from the UK Science and Technology Facilities Council.\r\n\r\nThe Low-Resolution Spectrograph 2 (LRS2) on HET was developed and funded by the University of Texas at Austin McDonald Observatory and Department of Astronomy, and by Pennsylvania State University. We thank the Leibniz-Institut für Astrophysik Potsdam (AIP) and the Institut für Astrophysik Göttingen (IAG) for their contributions to the construction of the integral field units. We acknowledge the Texas Advanced Computing Center (TACC) at The University of Texas at Austin for providing high performance computing, visualization, and storage resources that have contributed to the results reported within this paper.\r\n\r\nWe thank the anonymous referee for the detailed comments, which improved the clarity of the manuscript significantly. We also thank Gunter Cibis for pointing out typographical errors in the names of a few PNe in the first draft. S.B. expresses gratitude to Kishalay De for providing the Gattini-IR and WISE data. S.B. thanks Frank J. Masci and Zachary P. Vanderbosch for useful discussions and suggestions regarding solving the issues with ZTF forced photometry on extended sources. S.B. also thanks Jim Fuller, Charles C. Steidel, Lynne Hillenbrand, and Adolfo Carvalho for useful discussions on methods and science. S.B. also thanks David O. Cook for providing access to his CLU image cutout service to generate the WeSb 1 image. S.B. acknowledges the financial support from the Wallace L. W. Sargent Graduate Fellowship during the first year of his graduate studies at Caltech. N.C. was supported through the Cancer Research UK grant A24042. S.B. thanks Martina Veresvarka for drawing our attention to the TESS light curves of WeSb 1.\r\n\r\nWe have used Python packages Numpy (Harris et al. 2020), SciPy (Virtanen et al. 2020), Matplotlib (Hunter 2007), Pandas (pandas development team 2020), Astropy (Astropy Collaboration et al. 2013, 2018), and Astroquery (Ginsburg et al. 2019) at various stages of this research." article_number: '024201' article_processing_charge: No article_type: original arxiv: 1 author: - first_name: Soumyadeep full_name: Bhattacharjee, Soumyadeep last_name: Bhattacharjee - first_name: S. R. full_name: Kulkarni, S. R. last_name: Kulkarni - first_name: Albert K.H. full_name: Kong, Albert K.H. last_name: Kong - first_name: M. S. full_name: Tam, M. S. last_name: Tam - first_name: Howard E. full_name: Bond, Howard E. last_name: Bond - 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: Nicholas full_name: Chornay, Nicholas last_name: Chornay - first_name: Matthew J. full_name: Graham, Matthew J. last_name: Graham - first_name: Antonio C. full_name: Rodriguez, Antonio C. last_name: Rodriguez - first_name: Gregory R. full_name: Zeimann, Gregory R. last_name: Zeimann - first_name: Christoffer full_name: Fremling, Christoffer last_name: Fremling - first_name: Andrew J. full_name: Drake, Andrew J. last_name: Drake - first_name: Klaus full_name: Werner, Klaus last_name: Werner - first_name: Hector full_name: Rodriguez, Hector last_name: Rodriguez - first_name: Thomas A. full_name: Prince, Thomas A. last_name: Prince - first_name: Russ R. full_name: Laher, Russ R. last_name: Laher - first_name: Tracy X. full_name: Chen, Tracy X. last_name: Chen - first_name: Reed full_name: Riddle, Reed last_name: Riddle citation: ama: Bhattacharjee S, Kulkarni SR, Kong AKH, et al. Variability of central stars of planetary nebulae with the zwicky transient facility. I. Methods, short-timescale variables, and the unusual nucleus of WeSb 1. Publications of the Astronomical Society of the Pacific. 2025;137(2). doi:10.1088/1538-3873/ada702 apa: Bhattacharjee, S., Kulkarni, S. R., Kong, A. K. H., Tam, M. S., Bond, H. E., El-Badry, K., … Riddle, R. (2025). Variability of central stars of planetary nebulae with the zwicky transient facility. I. Methods, short-timescale variables, and the unusual nucleus of WeSb 1. Publications of the Astronomical Society of the Pacific. IOP Publishing. https://doi.org/10.1088/1538-3873/ada702 chicago: Bhattacharjee, Soumyadeep, S. R. Kulkarni, Albert K.H. Kong, M. S. Tam, Howard E. Bond, Kareem El-Badry, Ilaria Caiazzo, et al. “Variability of Central Stars of Planetary Nebulae with the Zwicky Transient Facility. I. Methods, Short-Timescale Variables, and the Unusual Nucleus of WeSb 1.” Publications of the Astronomical Society of the Pacific. IOP Publishing, 2025. https://doi.org/10.1088/1538-3873/ada702. ieee: S. Bhattacharjee et al., “Variability of central stars of planetary nebulae with the zwicky transient facility. I. Methods, short-timescale variables, and the unusual nucleus of WeSb 1,” Publications of the Astronomical Society of the Pacific, vol. 137, no. 2. IOP Publishing, 2025. ista: Bhattacharjee S, Kulkarni SR, Kong AKH, Tam MS, Bond HE, El-Badry K, Caiazzo I, Chornay N, Graham MJ, Rodriguez AC, Zeimann GR, Fremling C, Drake AJ, Werner K, Rodriguez H, Prince TA, Laher RR, Chen TX, Riddle R. 2025. Variability of central stars of planetary nebulae with the zwicky transient facility. I. Methods, short-timescale variables, and the unusual nucleus of WeSb 1. Publications of the Astronomical Society of the Pacific. 137(2), 024201. mla: Bhattacharjee, Soumyadeep, et al. “Variability of Central Stars of Planetary Nebulae with the Zwicky Transient Facility. I. Methods, Short-Timescale Variables, and the Unusual Nucleus of WeSb 1.” Publications of the Astronomical Society of the Pacific, vol. 137, no. 2, 024201, IOP Publishing, 2025, doi:10.1088/1538-3873/ada702. short: S. Bhattacharjee, S.R. Kulkarni, A.K.H. Kong, M.S. Tam, H.E. Bond, K. El-Badry, I. Caiazzo, N. Chornay, M.J. Graham, A.C. Rodriguez, G.R. Zeimann, C. Fremling, A.J. Drake, K. Werner, H. Rodriguez, T.A. Prince, R.R. Laher, T.X. Chen, R. Riddle, Publications of the Astronomical Society of the Pacific 137 (2025). das_tickbox: '1' date_created: 2025-02-16T23:02:33Z date_published: 2025-02-01T00:00:00Z date_updated: 2026-07-22T06:39:53Z day: '01' ddc: - '520' department: - _id: IlCa doi: 10.1088/1538-3873/ada702 external_id: arxiv: - '2410.03589' isi: - '001416903300001' file: - access_level: open_access checksum: 42b942ee1bf32ed225024e168174be92 content_type: application/pdf creator: dernst date_created: 2025-02-17T09:13:41Z date_updated: 2025-02-17T09:13:41Z file_id: '19034' file_name: 2025_PASP_Bhattacharjee.pdf file_size: 3657568 relation: main_file success: 1 file_date_updated: 2025-02-17T09:13:41Z has_accepted_license: '1' intvolume: ' 137' isi: 1 issue: '2' language: - iso: eng license: https://creativecommons.org/licenses/by/3.0/ month: '02' oa: 1 oa_version: Published Version publication: Publications of the Astronomical Society of the Pacific publication_identifier: issn: - 0004-6280 issnl: - 0004-6280 publication_status: published publisher: IOP Publishing quality_controlled: '1' related_material: link: - relation: erratum url: https://doi.org/10.1088/1538-3873/adbcd8 scopus_import: '1' status: public title: Variability of central stars of planetary nebulae with the zwicky transient facility. I. Methods, short-timescale variables, and the unusual nucleus of WeSb 1 tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/3.0/legalcode name: Creative Commons Attribution 3.0 Unported (CC BY 3.0) short: CC BY (3.0) type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 137 year: '2025' ... --- OA_place: repository OA_type: green _id: '19639' abstract: - lang: eng text: "Magnetic interactions are thought to play a key role in the properties of many unconventional superconductors, including cuprates, iron pnictides, and square-planar nickelates. Superconductivity was also recently observed in the bilayer and trilayer Ruddlesden-Popper nickelates, the electronic structure of which is expected to differ from that of cuprates and square-planar nickelates. Here we study how electronic structure and magnetic interactions evolve with the number of layers, \U0001D45B, in thin film Ruddlesden-Popper nickelates Nd\U0001D45B+1⁢Ni\U0001D45B⁢O3⁢\U0001D45B+1 with \U0001D45B=1,3, and 5 using resonant inelastic x-ray scattering (RIXS). The RIXS spectra are consistent with a high-spin |3⁢\U0001D4518⁢ \U0001D43F̲⟩ electronic configuration, resembling that of La2−\U0001D465⁢Sr\U0001D465⁢NiO4 and the parent perovskite, NdNiO3. The magnetic excitations soften to lower energy in the structurally self-doped, higher-\U0001D45B films. Our observations confirm that structural tuning is an effective route for altering electronic properties, such as magnetic superexchange, in this prominent family of materials." acknowledgement: Work by S.F.R.T., D.R.B., J.P., V.B., M.P.M.D., and M.M. was supported by the U.S. Department of Energy (DOE), Division of Materials Science, under Contract No. DE-SC0012704. G.A.P. and D.F.S. are primarily supported by the DOE, Office of Basic Energy Sciences, Division of Materials Sciences and Engineering, under Grant No. DE-SC0021925, and by NSF Graduate Research Fellowship Grant No. DGE-1745303. S.F.R.T. acknowledges additional support from the DOE, Office of Science, Office of Workforce Development for Teachers and Scientists, Office of Science Graduate Student Research (SCGSR) program. The SCGSR program is administered by the Oak Ridge Institute for Science and Education for the DOE under Contract No. DE-SC0014664. G.A.P. acknowledges additional support from the Paul and Daisy Soros Fellowship for New Americans. Q.S. was supported by the Science and Technology Center for Integrated Quantum Materials, NSF Grant No. DMR-1231319. B.H.G and L.F.K. acknowledge support by PARADIM, NSF Grant No. DMR-2039380. J.A.M. acknowledges support from the DOE, Office of Basic Energy Sciences, Division of Materials Sciences and Engineering, under Grant No. DE-SC0021925. Materials growth and electron microscopy were supported by PARADIM under NSF Cooperative Agreement Grant No. DMR-2039380. Electron microscopy made use of the Cornell Center for Materials Research Shared Facilities. The Thermo Fisher Spectra 300 X-CFEG was acquired with support from PARADIM, an NSF Materials Innovation Platforms (Grant No. DMR-2039380), and Cornell University. The FEI Titan Themis 300 was acquired through Grant No. NSF-MRI-1429155, with additional support from Cornell University, the Weill Institute, and the Kavli Institute at Cornell University. The Thermo Fisher Helios G4 UX FIB was acquired with support by NSF Grant No. DMR-1539918. This research used beamline 2-ID of the National Synchrotron Light Source II, a DOE Office of Science User Facility operated for the DOE Office of Science by Brookhaven National Laboratory under Contract No. DE-SC0012704. We acknowledge Diamond Light Source for time on Beamline I21 under Proposal No. MM27484. article_number: '165145' article_processing_charge: No article_type: original arxiv: 1 author: - first_name: Sophia F.R. full_name: Tenhuisen, Sophia F.R. last_name: Tenhuisen - first_name: Grace A. full_name: Pan, Grace A. last_name: Pan - first_name: Qi full_name: Song, Qi last_name: Song - first_name: Denitsa Rangelova full_name: Baykusheva, Denitsa Rangelova id: 71b4d059-2a03-11ee-914d-dfa3beed6530 last_name: Baykusheva orcid: 0000-0002-7438-1139 - first_name: Dan full_name: Ferenc Segedin, Dan last_name: Ferenc Segedin - first_name: Berit H. full_name: Goodge, Berit H. last_name: Goodge - first_name: Hanjong full_name: Paik, Hanjong last_name: Paik - first_name: Jonathan full_name: Pelliciari, Jonathan last_name: Pelliciari - first_name: Valentina full_name: Bisogni, Valentina last_name: Bisogni - first_name: Yanhong full_name: Gu, Yanhong last_name: Gu - first_name: Stefano full_name: Agrestini, Stefano last_name: Agrestini - first_name: Abhishek full_name: Nag, Abhishek last_name: Nag - first_name: Mirian full_name: García-Fernández, Mirian last_name: García-Fernández - first_name: Ke Jin full_name: Zhou, Ke Jin last_name: Zhou - first_name: Lena F. full_name: Kourkoutis, Lena F. last_name: Kourkoutis - first_name: Charles M. full_name: Brooks, Charles M. last_name: Brooks - first_name: Julia A. full_name: Mundy, Julia A. last_name: Mundy - first_name: Mark P.M. full_name: Dean, Mark P.M. last_name: Dean - first_name: Matteo full_name: Mitrano, Matteo last_name: Mitrano citation: ama: Tenhuisen SFR, Pan GA, Song Q, et al. Magnetic excitations in Ndn+1Nin O3n+1 Ruddlesden-Popper nickelates observed via resonant inelastic x-ray scattering. Physical Review B. 2025;111(16). doi:10.1103/PhysRevB.111.165145 apa: Tenhuisen, S. F. R., Pan, G. A., Song, Q., Baykusheva, D. R., Ferenc Segedin, D., Goodge, B. H., … Mitrano, M. (2025). Magnetic excitations in Ndn+1Nin O3n+1 Ruddlesden-Popper nickelates observed via resonant inelastic x-ray scattering. Physical Review B. American Physical Society. https://doi.org/10.1103/PhysRevB.111.165145 chicago: Tenhuisen, Sophia F.R., Grace A. Pan, Qi Song, Denitsa Rangelova Baykusheva, Dan Ferenc Segedin, Berit H. Goodge, Hanjong Paik, et al. “Magnetic Excitations in Ndn+1Nin O3n+1 Ruddlesden-Popper Nickelates Observed via Resonant Inelastic x-Ray Scattering.” Physical Review B. American Physical Society, 2025. https://doi.org/10.1103/PhysRevB.111.165145. ieee: S. F. R. Tenhuisen et al., “Magnetic excitations in Ndn+1Nin O3n+1 Ruddlesden-Popper nickelates observed via resonant inelastic x-ray scattering,” Physical Review B, vol. 111, no. 16. American Physical Society, 2025. ista: Tenhuisen SFR, Pan GA, Song Q, Baykusheva DR, Ferenc Segedin D, Goodge BH, Paik H, Pelliciari J, Bisogni V, Gu Y, Agrestini S, Nag A, García-Fernández M, Zhou KJ, Kourkoutis LF, Brooks CM, Mundy JA, Dean MPM, Mitrano M. 2025. Magnetic excitations in Ndn+1Nin O3n+1 Ruddlesden-Popper nickelates observed via resonant inelastic x-ray scattering. Physical Review B. 111(16), 165145. mla: Tenhuisen, Sophia F. R., et al. “Magnetic Excitations in Ndn+1Nin O3n+1 Ruddlesden-Popper Nickelates Observed via Resonant Inelastic x-Ray Scattering.” Physical Review B, vol. 111, no. 16, 165145, American Physical Society, 2025, doi:10.1103/PhysRevB.111.165145. short: S.F.R. Tenhuisen, G.A. Pan, Q. Song, D.R. Baykusheva, D. Ferenc Segedin, B.H. Goodge, H. Paik, J. Pelliciari, V. Bisogni, Y. Gu, S. Agrestini, A. Nag, M. García-Fernández, K.J. Zhou, L.F. Kourkoutis, C.M. Brooks, J.A. Mundy, M.P.M. Dean, M. Mitrano, Physical Review B 111 (2025). das_tickbox: '1' date_created: 2025-05-04T22:02:31Z date_published: 2025-04-15T00:00:00Z date_updated: 2026-07-22T06:53:20Z day: '15' department: - _id: DeBa doi: 10.1103/PhysRevB.111.165145 external_id: arxiv: - '2504.07268' intvolume: ' 111' issue: '16' language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.48550/arXiv.2504.07268 month: '04' 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: Magnetic excitations in Ndn+1Nin O3n+1 Ruddlesden-Popper nickelates observed via resonant inelastic x-ray scattering type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 111 year: '2025' ... --- OA_type: closed access _id: '20054' article_number: '220' article_processing_charge: No author: - first_name: Sharona full_name: Horta, Sharona id: 03a7e858-01b1-11ec-8b71-99ae6c4a05bc last_name: Horta citation: ama: 'Horta S. Solid state diffusion in metal-semiconductors core-shell nanoparticle. In: Proceedings of the MATSUS Spring 2025 Conference. Fundació de la comunitat valenciana SCITO; 2025. doi:10.29363/nanoge.matsusspring.2025.220' apa: 'Horta, S. (2025). Solid state diffusion in metal-semiconductors core-shell nanoparticle. In Proceedings of the MATSUS Spring 2025 Conference. Sevilla, Spain: Fundació de la comunitat valenciana SCITO. https://doi.org/10.29363/nanoge.matsusspring.2025.220' chicago: Horta, Sharona. “Solid State Diffusion in Metal-Semiconductors Core-Shell Nanoparticle.” In Proceedings of the MATSUS Spring 2025 Conference. Fundació de la comunitat valenciana SCITO, 2025. https://doi.org/10.29363/nanoge.matsusspring.2025.220. ieee: S. Horta, “Solid state diffusion in metal-semiconductors core-shell nanoparticle,” in Proceedings of the MATSUS Spring 2025 Conference, Sevilla, Spain, 2025. ista: 'Horta S. 2025. Solid state diffusion in metal-semiconductors core-shell nanoparticle. Proceedings of the MATSUS Spring 2025 Conference. MATSUS: Materials for Sustainable Development Conference, 220.' mla: Horta, Sharona. “Solid State Diffusion in Metal-Semiconductors Core-Shell Nanoparticle.” Proceedings of the MATSUS Spring 2025 Conference, 220, Fundació de la comunitat valenciana SCITO, 2025, doi:10.29363/nanoge.matsusspring.2025.220. short: S. Horta, in:, Proceedings of the MATSUS Spring 2025 Conference, Fundació de la comunitat valenciana SCITO, 2025. conference: end_date: 2025-03-07 location: Sevilla, Spain name: 'MATSUS: Materials for Sustainable Development Conference' start_date: 2025-03-03 corr_author: '1' date_created: 2025-07-21T08:22:29Z date_published: 2025-03-03T00:00:00Z date_updated: 2026-07-22T06:54:55Z day: '03' department: - _id: MaIb doi: 10.29363/nanoge.matsusspring.2025.220 language: - iso: eng month: '03' oa_version: None publication: Proceedings of the MATSUS Spring 2025 Conference publication_status: published publisher: Fundació de la comunitat valenciana SCITO quality_controlled: '1' status: public title: Solid state diffusion in metal-semiconductors core-shell nanoparticle type: conference_abstract user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2025' ... --- DOAJ_listed: '1' OA_place: publisher OA_type: gold _id: '20043' abstract: - lang: eng text: We establish an isomorphism of complex K-theory of the moduli space M of “SL n​ ”-Higgs bundles of degree d and rank n (in the sense of Hausel–Thaddeus) and twisted complex K-theory of the orbifold M of PGL n​ -Higgs bundles of degree e, where (n,d)=(n,e)=1. Along the way, we prove the vanishing of torsion for H ∗ ( M ) and certain twisted complex K-theory groups of M . We also extend Arinkin’s autoduality of compactified Jacobian to a derived equivalence between SL n​ - and PGL n​ -Hitchin systems over the elliptic locus. In the appendix, we develop a formalism of G-sheaves of spectra, generalising equivariant homotopy theory to a relative setting. acknowledgement: "It is a pleasure to thank Tom Baird for sharing his insights about vanishing of torsion for H.M{1\r\n2/. Furthermore, we would like to thank him for bringing [25] to our attention. We also thank Alexander Kupers for enlightening conversations about the Atiyah–Hirzebruch spectral sequence and for pointing out a reference. We are grateful to Victoria Hoskins and Simon Pepin-Lehalleur for sharing a preprint of their recent paper on a motivic version of topological mirror symmetry and for useful remarks on Section 6. Anne Larsen pointed out that our previous proof Lemma 4.5 was incomplete, we thank her for bringing this to our attention. We are grateful to the anonymous referee for many valuable comments that have improved the paper tremendously. The report we received was one of the most detailed referee report either of us has ever seen. We thank them for their hard work and the resulting contribution to this paper. Michael Groechenig was supported by an NSERC discovery grant and an Alfred P. Sloan\r\nfellowship. Shiyu Shen has received funding from the European Union’s Horizon 2020 research\r\nand innovation program under the Marie Skłodowska-Curie grant agreement No. 101034413." article_processing_charge: Yes article_type: original arxiv: 1 author: - first_name: Michael full_name: Groechenig, Michael last_name: Groechenig - first_name: Shiyu full_name: Shen, Shiyu id: 544cccd3-9005-11ec-87bc-94aef1c5b814 last_name: Shen orcid: 0000-0002-4444-8718 citation: ama: Groechenig M, Shen S. Complex K-theory of moduli spaces of Higgs bundles. Journal of the European Mathematical Society. 2025. doi:10.4171/jems/1601 apa: Groechenig, M., & Shen, S. (2025). Complex K-theory of moduli spaces of Higgs bundles. Journal of the European Mathematical Society. EMS Press. https://doi.org/10.4171/jems/1601 chicago: Groechenig, Michael, and Shiyu Shen. “Complex K-Theory of Moduli Spaces of Higgs Bundles.” Journal of the European Mathematical Society. EMS Press, 2025. https://doi.org/10.4171/jems/1601. ieee: M. Groechenig and S. Shen, “Complex K-theory of moduli spaces of Higgs bundles,” Journal of the European Mathematical Society. EMS Press, 2025. ista: Groechenig M, Shen S. 2025. Complex K-theory of moduli spaces of Higgs bundles. Journal of the European Mathematical Society. mla: Groechenig, Michael, and Shiyu Shen. “Complex K-Theory of Moduli Spaces of Higgs Bundles.” Journal of the European Mathematical Society, EMS Press, 2025, doi:10.4171/jems/1601. short: M. Groechenig, S. Shen, Journal of the European Mathematical Society (2025). corr_author: '1' das_tickbox: '1' date_created: 2025-07-21T07:54:50Z date_published: 2025-03-20T00:00:00Z date_updated: 2026-07-23T11:16:00Z day: '20' ddc: - '510' department: - _id: TaHa doi: 10.4171/jems/1601 ec_funded: 1 external_id: arxiv: - '2212.10695' isi: - '001608254800001' isi: 1 language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.4171/JEMS/1601 mathsc: - 14H60 - 19L50 month: '03' oa: 1 oa_version: Published Version project: - _id: fc2ed2f7-9c52-11eb-aca3-c01059dda49c call_identifier: H2020 grant_number: '101034413' name: 'IST-BRIDGE: International postdoctoral program' publication: Journal of the European Mathematical Society publication_identifier: eissn: - 1435-9863 issn: - 1435-9855 publication_status: epub_ahead publisher: EMS Press quality_controlled: '1' status: public title: Complex K-theory of moduli spaces of Higgs bundles type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2025' ... --- OA_place: publisher OA_type: hybrid _id: '20051' abstract: - lang: eng text: "We revisit the majority problem in the population protocol communication model, as first studied by Angluin et al. (Distributed Computing 2008). We consider a more general version of this problem known as plurality consensus, which has already been studied intensively in the literature. In this problem, each node in a system of n nodes, has initially one of k different opinions, and they need to agree on the (relative) majority opinion. In particular, we consider the important and intensively studied model of Undecided State Dynamics.\r\nOur main contribution is an almost tight lower bound on the stabilization time: we prove that there exists an initial configuration, even with bias \\Delta = \\omega(\\sqrt{n\\log n}), where stabilization requires \\Omega(kn\\log \\frac {\\sqrt n} {k \\log n}) interactions, or equivalently, \\Omega(k\\log \\frac {\\sqrt n} {k \\log n}) parallel time for any k = o\\left(\\frac {\\sqrt n}{\\log n}\\right). This bound is tight for any k \\le n^{\\frac 1 2 - \\epsilon}, where \\epsilon >0 can be any small constant, as Amir et al.~(PODC'23) gave a O(k\\log n) parallel time upper bound for k = O\\left(\\frac {\\sqrt n} {\\log ^2 n}\\right)." acknowledgement: "This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (MoDynStruct, No. 101019564) and the Austrian Science Fund (FWF) grant DOI 10.55776/I5862,grant DOI 10.55776/I5982, and grant DOI 10.55776/P33775 with\r\nadditional funding from the netidee SCIENCE Stiftung, 2020–2024\r\nand the German Research Foundation (DFG), grant 470029389\r\n(FlexNets)." article_processing_charge: Yes (via OA deal) arxiv: 1 author: - first_name: Antoine full_name: El-Hayek, Antoine id: 888a098e-fcac-11ee-aff7-d347be57b725 last_name: El-Hayek orcid: 0000-0003-4268-7368 - first_name: Robert full_name: Elsässer, Robert last_name: Elsässer - first_name: Stefan full_name: Schmid, Stefan last_name: Schmid citation: ama: 'El-Hayek A, Elsässer R, Schmid S. An almost tight lower bound for plurality consensus with undecided state dynamics in the population protocol model. In: Proceedings of the ACM Symposium on Principles of Distributed Computing. Association for Computing Machinery; 2025. doi:10.1145/3732772.3733505' apa: 'El-Hayek, A., Elsässer, R., & Schmid, S. (2025). An almost tight lower bound for plurality consensus with undecided state dynamics in the population protocol model. In Proceedings of the ACM Symposium on Principles of Distributed Computing. Huatulco, Mexico: Association for Computing Machinery. https://doi.org/10.1145/3732772.3733505' chicago: El-Hayek, Antoine, Robert Elsässer, and Stefan Schmid. “An Almost Tight Lower Bound for Plurality Consensus with Undecided State Dynamics in the Population Protocol Model.” In Proceedings of the ACM Symposium on Principles of Distributed Computing. Association for Computing Machinery, 2025. https://doi.org/10.1145/3732772.3733505. ieee: A. El-Hayek, R. Elsässer, and S. Schmid, “An almost tight lower bound for plurality consensus with undecided state dynamics in the population protocol model,” in Proceedings of the ACM Symposium on Principles of Distributed Computing, Huatulco, Mexico, 2025. ista: 'El-Hayek A, Elsässer R, Schmid S. 2025. An almost tight lower bound for plurality consensus with undecided state dynamics in the population protocol model. Proceedings of the ACM Symposium on Principles of Distributed Computing. PODC: Symposium on Principles of Distributed Computing.' mla: El-Hayek, Antoine, et al. “An Almost Tight Lower Bound for Plurality Consensus with Undecided State Dynamics in the Population Protocol Model.” Proceedings of the ACM Symposium on Principles of Distributed Computing, Association for Computing Machinery, 2025, doi:10.1145/3732772.3733505. short: A. El-Hayek, R. Elsässer, S. Schmid, in:, Proceedings of the ACM Symposium on Principles of Distributed Computing, Association for Computing Machinery, 2025. conference: end_date: 2025-06-20 location: Huatulco, Mexico name: 'PODC: Symposium on Principles of Distributed Computing' start_date: 2025-06-16 corr_author: '1' date_created: 2025-07-21T08:16:15Z date_published: 2025-06-13T00:00:00Z date_updated: 2026-07-24T12:48:28Z day: '13' ddc: - '000' department: - _id: MoHe doi: 10.1145/3732772.3733505 ec_funded: 1 external_id: arxiv: - '2505.02765' isi: - '001525534800066' file: - access_level: open_access checksum: 52976d226f3f691aa519d71c1c718fa5 content_type: application/pdf creator: dernst date_created: 2025-08-04T09:10:55Z date_updated: 2025-08-04T09:10:55Z file_id: '20115' file_name: 2025_PODC_ElHayek.pdf file_size: 2200347 relation: main_file success: 1 file_date_updated: 2025-08-04T09:10:55Z has_accepted_license: '1' isi: 1 language: - iso: eng month: '06' oa: 1 oa_version: Published Version project: - _id: bd9ca328-d553-11ed-ba76-dc4f890cfe62 call_identifier: H2020 grant_number: '101019564' name: The design and evaluation of modern fully dynamic data structures - _id: bda196b2-d553-11ed-ba76-8e8ee6c21103 grant_number: I05982 name: Static and Dynamic Hierarchical Graph Decompositions - _id: bd9e3a2e-d553-11ed-ba76-8aa684ce17fe grant_number: P33775 name: Fast Algorithms for a Reactive Network Layer publication: Proceedings of the ACM Symposium on Principles of Distributed Computing publication_identifier: isbn: - ' 9798400718854' publication_status: published publisher: Association for Computing Machinery quality_controlled: '1' related_material: record: - id: '22281' relation: dissertation_contains status: public status: public title: An almost tight lower bound for plurality consensus with undecided state dynamics in the population protocol model tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2025' ... --- OA_place: repository OA_type: green _id: '19982' abstract: - lang: eng text: "Dynamically maintaining the minimum cut in a graph G under edge insertions and deletion is a fundamental problem in dynamic graph algorithms for which no conditional lower bound on the time per operation exists. In an n-node graph the best known (1 + o (1))-approximate algorithm takes update time [14]. If the minimum cut is guaranteed to be (log n )o (1), a deterministic exact algorithm with n o (1) update time exists [8].\r\nWe present the first fully dynamic algorithm for (1 + o (1))-approximate minimum cut with n o(1) update time. Our main technical contribution is to show that it suffices to consider small-volume cuts in suitably contracted graphs." acknowledgement: This project has received funding from the European Research Council (ERC) under the European Union’sHorizon 2020 research and innovation programme (MoDynStruct, No. 101019564) and the Austrian Science Fund(FWF) grant DOI 10.55776/Z422, grant DOI 10.55776/I5982, and grant DOI 10.55776/P33775 with additional funding from the netidee SCIENCE Stiftung, 2020–2024. article_processing_charge: No arxiv: 1 author: - first_name: Antoine full_name: El-Hayek, Antoine id: 888a098e-fcac-11ee-aff7-d347be57b725 last_name: El-Hayek orcid: 0000-0003-4268-7368 - first_name: Monika H full_name: Henzinger, Monika H id: 540c9bbd-f2de-11ec-812d-d04a5be85630 last_name: Henzinger orcid: 0000-0002-5008-6530 - first_name: Jason full_name: Li, Jason last_name: Li citation: ama: 'El-Hayek A, Henzinger M, Li J. Fully dynamic approximate minimum cut in subpolynomial time per operation. In: Proceedings of the 2025 Annual ACM-SIAM Symposium on Discrete Algorithms. Society for Industrial and Applied Mathematics; 2025:750-784. doi:10.1137/1.9781611978322.22' apa: 'El-Hayek, A., Henzinger, M., & Li, J. (2025). Fully dynamic approximate minimum cut in subpolynomial time per operation. In Proceedings of the 2025 Annual ACM-SIAM Symposium on Discrete Algorithms (pp. 750–784). New Orleans, LA, United States: Society for Industrial and Applied Mathematics. https://doi.org/10.1137/1.9781611978322.22' chicago: El-Hayek, Antoine, Monika Henzinger, and Jason Li. “Fully Dynamic Approximate Minimum Cut in Subpolynomial Time per Operation.” In Proceedings of the 2025 Annual ACM-SIAM Symposium on Discrete Algorithms, 750–84. Society for Industrial and Applied Mathematics, 2025. https://doi.org/10.1137/1.9781611978322.22. ieee: A. El-Hayek, M. Henzinger, and J. Li, “Fully dynamic approximate minimum cut in subpolynomial time per operation,” in Proceedings of the 2025 Annual ACM-SIAM Symposium on Discrete Algorithms, New Orleans, LA, United States, 2025, pp. 750–784. ista: 'El-Hayek A, Henzinger M, Li J. 2025. Fully dynamic approximate minimum cut in subpolynomial time per operation. Proceedings of the 2025 Annual ACM-SIAM Symposium on Discrete Algorithms. SODA: Symposium on Discrete Algorithms, 750–784.' mla: El-Hayek, Antoine, et al. “Fully Dynamic Approximate Minimum Cut in Subpolynomial Time per Operation.” Proceedings of the 2025 Annual ACM-SIAM Symposium on Discrete Algorithms, Society for Industrial and Applied Mathematics, 2025, pp. 750–84, doi:10.1137/1.9781611978322.22. short: A. El-Hayek, M. Henzinger, J. Li, in:, Proceedings of the 2025 Annual ACM-SIAM Symposium on Discrete Algorithms, Society for Industrial and Applied Mathematics, 2025, pp. 750–784. conference: end_date: 2025-01-15 location: New Orleans, LA, United States name: 'SODA: Symposium on Discrete Algorithms' start_date: 2025-01-12 corr_author: '1' date_created: 2025-07-10T13:08:57Z date_published: 2025-01-07T00:00:00Z date_updated: 2026-07-24T12:48:28Z day: '07' department: - _id: MoHe doi: 10.1137/1.9781611978322.22 ec_funded: 1 external_id: arxiv: - '2412.15069' language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.48550/arXiv.2412.15069 month: '01' oa: 1 oa_version: Preprint page: 750-784 project: - _id: bd9ca328-d553-11ed-ba76-dc4f890cfe62 call_identifier: H2020 grant_number: '101019564' name: The design and evaluation of modern fully dynamic data structures - _id: 34def286-11ca-11ed-8bc3-da5948e1613c grant_number: Z00422 name: Efficient algorithms - _id: bda196b2-d553-11ed-ba76-8e8ee6c21103 grant_number: I05982 name: Static and Dynamic Hierarchical Graph Decompositions - _id: bd9e3a2e-d553-11ed-ba76-8aa684ce17fe grant_number: P33775 name: Fast Algorithms for a Reactive Network Layer publication: Proceedings of the 2025 Annual ACM-SIAM Symposium on Discrete Algorithms publication_identifier: eisbn: - '9781611978322' publication_status: published publisher: Society for Industrial and Applied Mathematics quality_controlled: '1' related_material: record: - id: '22281' relation: dissertation_contains status: public status: public title: Fully dynamic approximate minimum cut in subpolynomial time per operation type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2025' ... --- DOAJ_listed: '1' OA_place: publisher OA_type: gold PlanS_conform: '1' _id: '20669' abstract: - lang: eng text: 'Ice cliffs and supraglacial ponds are key drivers of mass loss on debris-covered glaciers. However, the relationship between melt ponds and adjacent ice cliffs has not been fully explored. We investigated the seasonal drainage patterns of a melt pond on the debris-covered Zhuxi Glacier in southeast Tibet and estimated the mass loss of its adjacent ice cliff during 2023-2024. Using hourly time-lapse photogrammetry we built a series of high-resolution point clouds to quantify the evolution of the ice cliff-pond system. Our findings indicate that subaerial melting and undercutting were the primary mechanisms of ice cliff mass loss during summer. In winter when the pond water level dropped, ice cliff calving became the dominant mode of ice loss. As the water level rose in spring, calving and subaerial melting occurred simultaneously and ice loss from calving accounted for approximately 19.5 % of total ice loss from February to July 2024. Our results reveal the transitional state of this ice cliff-pond system, exhibiting characteristics of both melt hotspots and lake-terminating calving fronts, and highlight the interplay between seasonal drainage-refill pond and differing modes of ice loss on adjacent ice cliff. Future research should focus on additional high-resolution monitoring of similar systems and incorporation of ice cliff-pond dynamics in glacier-scale numerical models. ' acknowledgement: This study was supported by the National Natural Science Foundation of China (grant nos. 42271138, 42201144), Lhasa Science and Technology Plan Project (LSKJ202406), the National Key R&D Program of China (grant nos. 2024YFF0808601), and the Science and Technology Plan Projects of Tibet Autonomous Region (Grants XZ202501ZY0081 and XZ202401ZY0003). ZH additionally acknowledges mobility funding provided by China Scholarship Council (CSC), supporting an extended research stay at the University of Plymouth, where much of this research was completed. article_number: e129 article_processing_charge: Yes article_type: original author: - first_name: Zhen full_name: He, Zhen last_name: He - first_name: Matthew full_name: Westoby, Matthew last_name: Westoby - first_name: Shaoting full_name: Ren, Shaoting id: 2066b6dd-2d54-11ef-8f8c-c94731161817 last_name: Ren - first_name: Chuanxi full_name: Zhao, Chuanxi last_name: Zhao - first_name: Yifei full_name: He, Yifei last_name: He - first_name: Tianzhao full_name: Zhang, Tianzhao last_name: Zhang - first_name: Wei full_name: Yang, Wei last_name: Yang citation: ama: He Z, Westoby M, REN S, et al. Quantifying the seasonal dynamics of a transitional ice cliff-pond system on a debris-covered glacier. Journal of Glaciology. 2025;71. doi:10.1017/jog.2025.10104 apa: He, Z., Westoby, M., REN, S., Zhao, C., He, Y., Zhang, T., & Yang, W. (2025). Quantifying the seasonal dynamics of a transitional ice cliff-pond system on a debris-covered glacier. Journal of Glaciology. Cambridge University Press. https://doi.org/10.1017/jog.2025.10104 chicago: He, Zhen, Matthew Westoby, SHAOTING REN, Chuanxi Zhao, Yifei He, Tianzhao Zhang, and Wei Yang. “Quantifying the Seasonal Dynamics of a Transitional Ice Cliff-Pond System on a Debris-Covered Glacier.” Journal of Glaciology. Cambridge University Press, 2025. https://doi.org/10.1017/jog.2025.10104. ieee: Z. He et al., “Quantifying the seasonal dynamics of a transitional ice cliff-pond system on a debris-covered glacier,” Journal of Glaciology, vol. 71. Cambridge University Press, 2025. ista: He Z, Westoby M, REN S, Zhao C, He Y, Zhang T, Yang W. 2025. Quantifying the seasonal dynamics of a transitional ice cliff-pond system on a debris-covered glacier. Journal of Glaciology. 71, e129. mla: He, Zhen, et al. “Quantifying the Seasonal Dynamics of a Transitional Ice Cliff-Pond System on a Debris-Covered Glacier.” Journal of Glaciology, vol. 71, e129, Cambridge University Press, 2025, doi:10.1017/jog.2025.10104. short: Z. He, M. Westoby, S. REN, C. Zhao, Y. He, T. Zhang, W. Yang, Journal of Glaciology 71 (2025). das_tickbox: '1' dataavailabilitystatement: The Python scripts to processing of the time-lapse photos to point clouds, as well as ICP registration, are available on Zenodo (https://doi.org/10.5281/zenodo.16272541). date_created: 2025-11-23T23:01:40Z date_published: 2025-11-10T00:00:00Z date_updated: 2026-07-27T08:21:14Z day: '10' ddc: - '550' department: - _id: FrPe doi: 10.1017/jog.2025.10104 file: - access_level: open_access checksum: 6b50f39880c70b2e58baaa7713848ab5 content_type: application/pdf creator: dernst date_created: 2026-07-27T08:19:34Z date_updated: 2026-07-27T08:19:34Z file_id: '22411' file_name: 2026_JournalGlaciology_He.pdf file_size: 6023889 relation: main_file success: 1 file_date_updated: 2026-07-27T08:19:34Z has_accepted_license: '1' intvolume: ' 71' language: - iso: eng month: '11' oa: 1 oa_version: Published Version publication: Journal of Glaciology publication_identifier: eissn: - 1727-5652 issn: - 0022-1430 publication_status: published publisher: Cambridge University Press quality_controlled: '1' researchdata_availability: yes scopus_import: '1' status: public supplementarymaterial: no title: Quantifying the seasonal dynamics of a transitional ice cliff-pond system on a debris-covered glacier 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: 71 year: '2025' ... --- OA_place: publisher _id: '19759' abstract: - lang: eng text: "Despite generating remarkable results in various computer vision tasks, deep learning comes\r\nwith some surprising shortcomings. For example, tiny perturbations, often imperceptible to\r\nthe human eye, can completely change the predictions of image classifiers. Despite a decade\r\nof research, the field has made limited progress in developing image classifiers that are both\r\naccurate and robust. This thesis aims to address this gap.\r\nAs our first contribution, we aim to simplify the process of training certifiably robust image\r\nclassifiers. We do this by designing a convolutional layer that does not require executing an\r\niterative procedure in every forward pass, but relies on an explicit bound instead. We also\r\npropose a loss function that allows optimizing for a particular margin more precisely.\r\nNext, we provide an overview and comparison of various methods that create robust image\r\nclassifiers by constraining the Lipschitz constant. This is important since generally longer\r\ntraining times and more parameters improve the performance of robust classifiers, making it\r\nchallenging to determine the most practical and effective methods from existing literature.\r\nIn 1-Lipschitz classification, the performance of current methods is still much worse than what\r\nwe expect on the simple tasks we consider. Therefore, we next investigate potential causes of\r\nthis shortcoming. We first consider the role of the activation function. We prove a theoretical\r\nshortcoming of the commonly used activation function, and provide an alternative without it.\r\nHowever this theoretical improvement does barely translate to the empirical performance of\r\nrobust classifiers, suggesting a different bottleneck.\r\nTherefore, in the final chapter, we study how the performance depends on the amount of\r\ntraining data. We prove that in the worst case, we might require far more data to train a\r\nrobust classifier compared to a normal one. We furthermore find that the amount of training\r\ndata is a key determinant of the performance current methods achieve on popular datasets.\r\nAdditionally, we show that linear subspaces exist with tiny data variance, and yet we can\r\nstill train very accurate classifiers after projecting into those subspaces. This shows that on\r\nthe datasets considered, enforcing robustness in classification makes the task strictly more\r\nchallenging.\r\n\r\n" alternative_title: - ISTA Thesis article_processing_charge: No author: - first_name: Bernd full_name: Prach, Bernd id: 2D561D42-C427-11E9-89B4-9C1AE6697425 last_name: Prach citation: ama: Prach B. Robust image classification with 1-Lipschitz networks. 2025. doi:10.15479/10.15479/at-ista-19759 apa: Prach, B. (2025). Robust image classification with 1-Lipschitz networks. Institute of Science and Technology Austria. https://doi.org/10.15479/10.15479/at-ista-19759 chicago: Prach, Bernd. “Robust Image Classification with 1-Lipschitz Networks.” Institute of Science and Technology Austria, 2025. https://doi.org/10.15479/10.15479/at-ista-19759. ieee: B. Prach, “Robust image classification with 1-Lipschitz networks,” Institute of Science and Technology Austria, 2025. ista: Prach B. 2025. Robust image classification with 1-Lipschitz networks. Institute of Science and Technology Austria. mla: Prach, Bernd. Robust Image Classification with 1-Lipschitz Networks. Institute of Science and Technology Austria, 2025, doi:10.15479/10.15479/at-ista-19759. short: B. Prach, Robust Image Classification with 1-Lipschitz Networks, Institute of Science and Technology Austria, 2025. corr_author: '1' date_created: 2025-05-28T16:20:48Z date_published: 2025-05-30T00:00:00Z date_updated: 2026-07-27T12:47:44Z day: '30' ddc: - '000' degree_awarded: PhD department: - _id: GradSch - _id: ChLa doi: 10.15479/10.15479/at-ista-19759 doi_confirm: '1' file: - access_level: open_access checksum: e5108e759014e2a9020c973c778fafc9 content_type: application/pdf creator: bprach date_created: 2025-06-10T18:11:05Z date_updated: 2025-06-10T18:11:05Z file_id: '19829' file_name: ThesisFinal.pdf file_size: 3578077 relation: main_file - access_level: closed checksum: 51bf6c11fb6d8a9f8010b458c600a83f content_type: application/x-zip-compressed creator: bprach date_created: 2025-06-10T18:14:03Z date_updated: 2025-06-10T18:14:03Z file_id: '19830' file_name: ThesisFinal.zip file_size: 74894357 relation: source_file file_date_updated: 2025-06-10T18:14:03Z has_accepted_license: '1' language: - iso: eng month: '05' oa: 1 oa_version: Published Version page: '84' publication_identifier: issn: - 2663-337X publication_status: published publisher: Institute of Science and Technology Austria publisher_comment: "In reference to IEEE copyrighted material which is used with permission in this thesis, the IEEE does not\r\nendorse any of ISTA's products or services. Internal or personal use of this\r\nmaterial is permitted. If interested in reprinting/republishing IEEE copyrighted material for advertising or promotional\r\npurposes or for creating new collective works for resale or redistribution, please go to\r\nhttp://www.ieee.org/publications_standards/publications/rights/rights_link.html to learn how to obtain a License from\r\nRightsLink. If applicable, University Microfilms and/or ProQuest Library, or the Archives of Canada may supply single copies of the dissertation." related_material: record: - id: '15039' relation: part_of_dissertation status: public - id: '18874' relation: part_of_dissertation status: public - id: '17426' relation: part_of_dissertation status: public - id: '11839' relation: part_of_dissertation status: public status: public supervisor: - first_name: Christoph full_name: Lampert, Christoph id: 40C20FD2-F248-11E8-B48F-1D18A9856A87 last_name: Lampert orcid: 0000-0001-8622-7887 title: Robust image classification with 1-Lipschitz networks type: dissertation user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9 year: '2025' ... --- OA_place: publisher OA_type: hybrid _id: '19741' abstract: - lang: eng text: 'Quantitative automata model beyond-boolean aspects of systems: every execution is mapped to a real number by incorporating weighted transitions and value functions that generalize acceptance conditions of boolean w-automata. Despite the theoretical advances in systems analysis through quantitative automata, the first comprehensive software tool for quantitative automata (Quantitative Automata Kit, or QuAK) was developed only recently. QuAK implements algorithms for solving standard decision problems, e.g., emptiness and universality, as well as constructions for safety and liveness of quantitative automata. We present the architecture of QuAK, which reflects that all of these problems reduce to either checking inclusion between two quantitative automata or computing the highest value achievable by an automaton—its so-called top value. We improve QuAK by extending these two algorithms with an option to return, alongside their results, an ultimately periodic word witnessing the algorithm’s output, as well as implementing a new safety-liveness decomposition algorithm that can handle nondeterministic automata, making QuAK more informative and capable.' acknowledgement: This work was supported in part by the ERC-2020-AdG 101020093. alternative_title: - LNCS article_processing_charge: No arxiv: 1 author: - first_name: Marek full_name: Chalupa, Marek id: 87e34708-d6c6-11ec-9f5b-9391e7be2463 last_name: Chalupa - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000-0002-2985-7724 - first_name: Nicolas Adrien full_name: Mazzocchi, Nicolas Adrien id: b26baa86-3308-11ec-87b0-8990f34baa85 last_name: Mazzocchi - first_name: Naci E full_name: Sarac, Naci E id: 8C6B42F8-C8E6-11E9-A03A-F2DCE5697425 last_name: Sarac citation: ama: 'Chalupa M, Henzinger TA, Mazzocchi NA, Sarac NE. Automating the analysis of quantitative automata with QuAK. In: 31st International Conference on Tools and Algorithms for the Construction and Analysis of Systems. Vol 15696. Springer Nature; 2025:303-312. doi:10.1007/978-3-031-90643-5_16' apa: Chalupa, M., Henzinger, T. A., Mazzocchi, N. A., & Sarac, N. E. (2025). Automating the analysis of quantitative automata with QuAK. In 31st International Conference on Tools and Algorithms for the Construction and Analysis of Systems (Vol. 15696, pp. 303–312). Springer Nature. https://doi.org/10.1007/978-3-031-90643-5_16 chicago: Chalupa, Marek, Thomas A Henzinger, Nicolas Adrien Mazzocchi, and Naci E Sarac. “Automating the Analysis of Quantitative Automata with QuAK.” In 31st International Conference on Tools and Algorithms for the Construction and Analysis of Systems, 15696:303–12. Springer Nature, 2025. https://doi.org/10.1007/978-3-031-90643-5_16. ieee: M. Chalupa, T. A. Henzinger, N. A. Mazzocchi, and N. E. Sarac, “Automating the analysis of quantitative automata with QuAK,” in 31st International Conference on Tools and Algorithms for the Construction and Analysis of Systems, 2025, vol. 15696, pp. 303–312. ista: Chalupa M, Henzinger TA, Mazzocchi NA, Sarac NE. 2025. Automating the analysis of quantitative automata with QuAK. 31st International Conference on Tools and Algorithms for the Construction and Analysis of Systems. , LNCS, vol. 15696, 303–312. mla: Chalupa, Marek, et al. “Automating the Analysis of Quantitative Automata with QuAK.” 31st International Conference on Tools and Algorithms for the Construction and Analysis of Systems, vol. 15696, Springer Nature, 2025, pp. 303–12, doi:10.1007/978-3-031-90643-5_16. short: M. Chalupa, T.A. Henzinger, N.A. Mazzocchi, N.E. Sarac, in:, 31st International Conference on Tools and Algorithms for the Construction and Analysis of Systems, Springer Nature, 2025, pp. 303–312. corr_author: '1' date_created: 2025-05-25T22:17:07Z date_published: 2025-05-01T00:00:00Z date_updated: 2026-07-27T12:48:18Z day: '01' ddc: - '000' department: - _id: ToHe doi: 10.1007/978-3-031-90643-5_16 ec_funded: 1 external_id: arxiv: - '2501.16088' file: - access_level: open_access checksum: a27fa245be8d83421e9127b48a09c8af content_type: application/pdf creator: dernst date_created: 2025-06-02T08:13:11Z date_updated: 2025-06-02T08:13:11Z file_id: '19768' file_name: 2025_TACAS_ChalupaMarek.pdf file_size: 420669 relation: main_file success: 1 file_date_updated: 2025-06-02T08:13:11Z has_accepted_license: '1' intvolume: ' 15696' language: - iso: eng month: '05' oa: 1 oa_version: Published Version page: 303-312 project: - _id: 62781420-2b32-11ec-9570-8d9b63373d4d call_identifier: H2020 grant_number: '101020093' name: Vigilant Algorithmic Monitoring of Software publication: 31st International Conference on Tools and Algorithms for the Construction and Analysis of Systems publication_identifier: eissn: - 1611-3349 isbn: - '9783031906428' issn: - 0302-9743 publication_status: published publisher: Springer Nature quality_controlled: '1' related_material: record: - id: '20147' relation: dissertation_contains status: public scopus_import: '1' status: public title: Automating the analysis of quantitative automata with QuAK 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: 15696 year: '2025' ... --- OA_place: repository OA_type: green _id: '21858' abstract: - lang: eng text: "The recent surge in high-quality open-source Generative AI text models (colloquially: LLMs), as well as efficient finetuning techniques, have opened the possibility of creating high-quality personalized models that generate text attuned to a specific individual’s needs and are capable of credibly imitating their writing style by refining an open-source model with that person’s own data. The technology to create such models is accessible to private individuals, and training and running such models can be done cheaply on consumer-grade hardware. While these advancements are a huge gain for usability and privacy, this position paper argues that the practical feasibility of impersonating specific individuals also introduces novel safety risks. For instance, this technology enables the creation of phishing emails\r\nor fraudulent social media accounts, based on small amounts of publicly available text, or by the individuals themselves to escape AI text detection. We further argue that these risks are complementary to—and distinct from—the much-discussed risks of other impersonation attacks such as image, voice, or video deepfakes, and are not adequately addressed by the larger research community, or the current generation of open- and closed-source models." acknowledgement: "This research was supported by the Scientific Service Units (SSU) of IST Austria through resources\r\nprovided by Scientific Computing (SciComp). EI was supported in part by the FWF DK VGSCO,\r\ngrant agreement number W1260-N35. AJ was supported in part by ERC Proof-of-Concept Grant\r\nFastML, grant agreement 101158077." article_processing_charge: No arxiv: 1 author: - first_name: Eugenia B full_name: Iofinova, Eugenia B id: f9a17499-f6e0-11ea-865d-fdf9a3f77117 last_name: Iofinova orcid: 0000-0002-7778-3221 - first_name: Andrej full_name: Jovanovic, Andrej last_name: Jovanovic - 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: 'Iofinova EB, Jovanovic A, Alistarh D-A. Position: It’s time to act on the risk of efficient personalized text generation. arXiv. doi:10.48550/arXiv.2502.06560' apa: 'Iofinova, E. B., Jovanovic, A., & Alistarh, D.-A. (n.d.). Position: It’s time to act on the risk of efficient personalized text generation. arXiv. https://doi.org/10.48550/arXiv.2502.06560' chicago: 'Iofinova, Eugenia B, Andrej Jovanovic, and Dan-Adrian Alistarh. “Position: It’s Time to Act on the Risk of Efficient Personalized Text Generation.” ArXiv, n.d. https://doi.org/10.48550/arXiv.2502.06560.' ieee: 'E. B. Iofinova, A. Jovanovic, and D.-A. Alistarh, “Position: It’s time to act on the risk of efficient personalized text generation,” arXiv. .' ista: 'Iofinova EB, Jovanovic A, Alistarh D-A. Position: It’s time to act on the risk of efficient personalized text generation. arXiv, 10.48550/arXiv.2502.06560.' mla: 'Iofinova, Eugenia B., et al. “Position: It’s Time to Act on the Risk of Efficient Personalized Text Generation.” ArXiv, doi:10.48550/arXiv.2502.06560.' short: E.B. Iofinova, A. Jovanovic, D.-A. Alistarh, ArXiv (n.d.). corr_author: '1' date_created: 2026-05-11T08:55:23Z date_published: 2025-06-02T00:00:00Z date_updated: 2026-07-27T12:50:03Z day: '02' department: - _id: GradSch - _id: DaAl doi: 10.48550/arXiv.2502.06560 external_id: arxiv: - '2502.06560' language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.48550/arXiv.2502.06560 month: '06' oa: 1 oa_version: Preprint project: - _id: 8e35c14b-16d5-11f0-9cad-a3fc35339161 grant_number: '101158077' name: 'FastML: Efficient and Cost-Effective Distributed Machine Learning' - _id: 9B9290DE-BA93-11EA-9121-9846C619BF3A grant_number: W1260-N35 name: Vienna Graduate School on Computational Optimization publication: arXiv publication_status: draft related_material: record: - id: '21854' relation: dissertation_contains status: public status: public title: 'Position: It''s time to act on the risk of efficient personalized text generation' type: preprint user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9 year: '2025' ... --- OA_place: publisher _id: '20138' abstract: - lang: eng text: "The evolution shapes the world around us.\r\nNot only in biology, where the fittest individuals spread their genes but also in physics and social dynamics, the evolutionary forces determine the development of a state of matter or public opinions.\r\nMany models describe these dynamics.\r\nThis thesis examines the role of the structure in the models of selection.\r\nThe population structure is represented as a graph or a network, and each vertex is occupied by one individual.\r\nEvery individual has a type and fitness that represents the reproductive potential and depends on the type, occupied vertex, and the arrangement of the neighbors.\r\nThe evolution is modeled in discrete steps; in one step, one individual is replaced by a neighbor selected randomly with the influence of fitness.\r\n\r\n\r\n\r\nThe role of the networks is widely examined in the literature.\r\nThe structures that promote the spread of the desired type compared to the structureless case are called amplifiers.\r\nThe existence of amplifiers in various settings is an intensively studied topic, and in some settings, the amplifiers have been identified.\r\nMoreover, there are other important questions about the number of steps until one type spreads over the whole network (fixation time), the computational complexity, and the questions about the robustness of these processes.\r\n\r\n\r\nThis thesis explores the role of structure in evolution from many perspectives.\r\nFirst, it introduces different models and various choices that can be made in the models of evolution.\r\nIt highlights the role of the structure in the real world and how this is reflected in these models.\r\nThen, it describes the previous results and open problems.\r\nSecond, the thesis describes an amplifier for two variants of the Moran process: one with a constant birth rate and the other with a constant death rate.\r\nThis is an important contribution to the robustness of the amplification.\r\nThird, the thesis determines the complexity of spatial games.\r\nThese are processes where the fitness comes from a game, and the strength of selection is high.\r\nIt shows that determining the fate of cooperation in these games is a PSPACE-complete problem.\r\nFourth, the thesis describes the amplifier of cooperation for spatial games.\r\nThis is the first amplifier in this setting.\r\nFifth, the thesis examines the coexistence in the Moran process with environmental heterogeneity.\r\nIn this setting, the fitness depends not only on the type of the individual but also on the occupied vertex.\r\nThe chapter determines the relationship between the interactions of vertices of different types and the coexistence time.\r\nSixth, the thesis examines the social balance on networks and proposes a stochastic dynamic partially aware of the state of the graph, which reaches a balanced position quickly.\r\nFinally, the thesis presents conclusions and outlines the directions for future work.\r\n\r\n\r\n" acknowledgement: "This work was supported by the European Research Council CoG 863818 (ForMSMArt) and Austrian Science Fund 10.55776/COE12.\r\n" alternative_title: - ISTA Thesis article_processing_charge: No author: - first_name: Jakub full_name: Svoboda, Jakub id: 130759D2-D7DD-11E9-87D2-DE0DE6697425 last_name: Svoboda orcid: 0000-0002-1419-3267 citation: ama: Svoboda J. Structural properties of games on graphs. 2025. doi:10.15479/AT-ISTA-20138 apa: Svoboda, J. (2025). Structural properties of games on graphs. Institute of Science and Technology Austria. https://doi.org/10.15479/AT-ISTA-20138 chicago: Svoboda, Jakub. “Structural Properties of Games on Graphs.” Institute of Science and Technology Austria, 2025. https://doi.org/10.15479/AT-ISTA-20138. ieee: J. Svoboda, “Structural properties of games on graphs,” Institute of Science and Technology Austria, 2025. ista: Svoboda J. 2025. Structural properties of games on graphs. Institute of Science and Technology Austria. mla: Svoboda, Jakub. Structural Properties of Games on Graphs. Institute of Science and Technology Austria, 2025, doi:10.15479/AT-ISTA-20138. short: J. Svoboda, Structural Properties of Games on Graphs, Institute of Science and Technology Austria, 2025. corr_author: '1' das_tickbox: '1' date_created: 2025-08-05T14:33:59Z date_published: 2025-08-05T00:00:00Z date_updated: 2026-07-27T12:52:04Z day: '05' ddc: - '000' - '519' degree_awarded: PhD department: - _id: GradSch - _id: KrCh doi: 10.15479/AT-ISTA-20138 doi_confirm: '1' ec_funded: 1 file: - access_level: open_access checksum: c6c4df9777f4537940de7ab392ad57e2 content_type: application/pdf creator: jsvoboda date_created: 2025-08-14T09:54:43Z date_updated: 2025-08-14T09:54:43Z file_id: '20177' file_name: 2025_Svoboda_Jakub_Thesis.pdf file_size: 5927291 relation: main_file success: 1 - access_level: closed checksum: 485e9f9822821bc03666d245d80aaa08 content_type: application/zip creator: jsvoboda date_created: 2025-08-14T09:55:20Z date_updated: 2025-08-21T11:48:39Z file_id: '20178' file_name: 2025_Svoboda_Jakub_Thesis.zip file_size: 6731815 relation: source_file file_date_updated: 2025-08-21T11:48:39Z has_accepted_license: '1' language: - iso: eng license: https://creativecommons.org/licenses/by-nc-sa/4.0/ month: '08' oa: 1 oa_version: Published Version page: '167' project: - _id: 0599E47C-7A3F-11EA-A408-12923DDC885E call_identifier: H2020 grant_number: '863818' name: 'Formal Methods for Stochastic Models: Algorithms and Applications' publication_identifier: issn: - 2663-337X publication_status: published publisher: Institute of Science and Technology Austria publisher_comment: "Chapter 4 is copyrighted by CC BY-NC-ND\r\n4.0, which prohibits derivatives. Chapter 6 is copyrighted: Copyright (2025) by the American\r\nPhysical Society. For a copy, redistribution, or modification needs to be permitted by the\r\nAmerican Physical Society.\r\n" related_material: record: - id: '12787' relation: part_of_dissertation status: public - id: '12101' relation: part_of_dissertation status: public - id: '12257' relation: part_of_dissertation status: public - id: '15297' relation: part_of_dissertation status: public - id: '18703' relation: part_of_dissertation status: public status: public supervisor: - first_name: Krishnendu full_name: Chatterjee, Krishnendu id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87 last_name: Chatterjee orcid: 0000-0002-4561-241X title: Structural properties of games on graphs tmp: image: /images/cc_by_nc_sa.png legal_code_url: https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode name: Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) short: CC BY-NC-SA (4.0) type: dissertation user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9 year: '2025' ... --- OA_place: repository OA_type: green _id: '21144' abstract: - lang: eng text: 'This paper deals with the algorithmic aspects of solving feasibility problems of semidefinite programming (SDP), aka linear matrix inequalities (LMIs). Since in some SDP instances all feasible solutions have irrational entries, numerical solvers that work with rational numbers can only find an approximate solution. We study the following question: Is it possible to certify feasibility of a given SDP using an approximate solution that is sufficiently close to some exact solution? Existing approaches make the assumption that there exist rational feasible solutions (and use techniques such as rounding and lattice reduction algorithms). We propose an alternative approach that does not need this assumption. More specifically, we show how to construct a system of polynomial equations whose set of real solutions is guaranteed to have an isolated correct solution (assuming that the target exact solution is maximum-rank). This allows, in particular, for us to use algorithms from real algebraic geometry for solving systems of polynomial equations, yielding a hybrid (or symbolic-numerical) method for SDPs. We experimentally compare it with a pure symbolic method in [D. Henrion, S. Naldi, and M. Safey El Din, SIAM J. Optim., 26 (2016), pp. 2512–2539]; the hybrid method was able to certify feasibility of many SDP instances on which the aforementioned paper failed. Our approach may have further applications, such as refining an approximate solution using methods of numerical algebraic geometry for systems of polynomial equations.' article_processing_charge: No article_type: original arxiv: 1 author: - first_name: Vladimir full_name: Kolmogorov, Vladimir id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87 last_name: Kolmogorov - first_name: Simone full_name: Naldi, Simone last_name: Naldi - first_name: Jeferson full_name: Zapata, Jeferson id: 00223538-AF8F-11E9-A4C7-F729E6697425 last_name: Zapata citation: ama: Kolmogorov V, Naldi S, Zapata J. Certifying solutions of degenerate semidefinite programs. SIAM Journal on Optimization. 2025;35(3):1630-1654. doi:10.1137/24m1664691 apa: Kolmogorov, V., Naldi, S., & Zapata, J. (2025). Certifying solutions of degenerate semidefinite programs. SIAM Journal on Optimization. Society for Industrial and Applied Mathematics. https://doi.org/10.1137/24m1664691 chicago: Kolmogorov, Vladimir, Simone Naldi, and Jeferson Zapata. “Certifying Solutions of Degenerate Semidefinite Programs.” SIAM Journal on Optimization. Society for Industrial and Applied Mathematics, 2025. https://doi.org/10.1137/24m1664691. ieee: V. Kolmogorov, S. Naldi, and J. Zapata, “Certifying solutions of degenerate semidefinite programs,” SIAM Journal on Optimization, vol. 35, no. 3. Society for Industrial and Applied Mathematics, pp. 1630–1654, 2025. ista: Kolmogorov V, Naldi S, Zapata J. 2025. Certifying solutions of degenerate semidefinite programs. SIAM Journal on Optimization. 35(3), 1630–1654. mla: Kolmogorov, Vladimir, et al. “Certifying Solutions of Degenerate Semidefinite Programs.” SIAM Journal on Optimization, vol. 35, no. 3, Society for Industrial and Applied Mathematics, 2025, pp. 1630–54, doi:10.1137/24m1664691. short: V. Kolmogorov, S. Naldi, J. Zapata, SIAM Journal on Optimization 35 (2025) 1630–1654. date_created: 2026-02-05T13:33:05Z date_published: 2025-09-01T00:00:00Z date_updated: 2026-07-27T14:30:41Z day: '01' department: - _id: VlKo - _id: GradSch doi: 10.1137/24m1664691 external_id: arxiv: - '2405.13625' intvolume: ' 35' issue: '3' language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.48550/arXiv.2405.13625 month: '09' oa: 1 oa_version: Preprint page: 1630-1654 publication: SIAM Journal on Optimization publication_identifier: eissn: - 1095-7189 issn: - 1052-6234 publication_status: published publisher: Society for Industrial and Applied Mathematics quality_controlled: '1' related_material: record: - id: '21957' relation: dissertation_contains status: public status: public title: Certifying solutions of degenerate semidefinite programs type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 35 year: '2025' ... --- OA_place: publisher OA_type: gold _id: '21074' abstract: - lang: eng text: Neural models learn representations of high-dimensional data on low-dimensional manifolds. Multiple factors, including stochasticities in the training process, model architectures, and additional inductive biases, may induce different representations, even when learning the same task on the same data. However, it has recently been shown that when a latent structure is shared between distinct latent spaces, relative distances between representations can be preserved, up to distortions. Building on this idea, we demonstrate that exploiting the differential-geometric structure of latent spaces of neural models, it is possible to capture precisely the transformations between representational spaces trained on similar data distributions. Specifically, we assume that distinct neural models parametrize approximately the same underlying manifold, and introduce a representation based on the pullback metric that captures the intrinsic structure of the latent space, while scaling efficiently to large models. We validate experimentally our method on model stitching and retrieval tasks, covering autoencoders and vision foundation discriminative models, across diverse architectures, datasets, pretraining schemes and modalities. Code is available at the following link. acknowledgement: 'We thank Gregor Krzmanc, German Magai, Vital Fernandez for insightful discussions in the early stages of the project. HY was supported by the Research Council of Finland Flagship programme: Finnish Center for Artificial Intelligence FCAI. HY wishes to acknowledge CSC - IT Center for Science, Finland, for computational resources. GA was supported by the DFF Sapere Aude Starting Grant “GADL”. SH was supported by a research grant (42062) from VILLUM FONDEN and partly funded by the Novo Nordisk Foundation through the Center for Basic Research in Life Science (NNF20OC0062606). SH received funding from the European Research Council (ERC) under the European Union’s Horizon Programme (grant agreement 101125003). MF is supported by the MSCA IST-Bridge fellowship which has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No 101034413.' alternative_title: - Advances in Neural Information Processing Systems article_processing_charge: No arxiv: 1 author: - first_name: Hanlin full_name: Yu, Hanlin last_name: Yu - first_name: Befrin full_name: Inal, Befrin last_name: Inal - first_name: Georgios full_name: Arvanitidis, Georgios last_name: Arvanitidis - first_name: Soren full_name: Hauberg, Soren last_name: Hauberg - first_name: Francesco full_name: Locatello, Francesco id: 26cfd52f-2483-11ee-8040-88983bcc06d4 last_name: Locatello orcid: 0000-0002-4850-0683 - first_name: Marco full_name: Fumero, Marco id: 1c1593eb-393f-11ef-bb8e-ab4f1e979650 last_name: Fumero citation: ama: 'Yu H, Inal B, Arvanitidis G, Hauberg S, Locatello F, Fumero M. Connecting neural models latent geometries with relative geodesic representations. In: 39th Annual Conference on Neural Information Processing Systems. Vol 38. Neural Information Processing Systems Foundation; 2025.' apa: 'Yu, H., Inal, B., Arvanitidis, G., Hauberg, S., Locatello, F., & Fumero, M. (2025). Connecting neural models latent geometries with relative geodesic representations. In 39th Annual Conference on Neural Information Processing Systems (Vol. 38). San Diego, CA, United States: Neural Information Processing Systems Foundation.' chicago: Yu, Hanlin, Befrin Inal, Georgios Arvanitidis, Soren Hauberg, Francesco Locatello, and Marco Fumero. “Connecting Neural Models Latent Geometries with Relative Geodesic Representations.” In 39th Annual Conference on Neural Information Processing Systems, Vol. 38. Neural Information Processing Systems Foundation, 2025. ieee: H. Yu, B. Inal, G. Arvanitidis, S. Hauberg, F. Locatello, and M. Fumero, “Connecting neural models latent geometries with relative geodesic representations,” in 39th Annual Conference on Neural Information Processing Systems, San Diego, CA, United States, 2025, vol. 38. ista: 'Yu H, Inal B, Arvanitidis G, Hauberg S, Locatello F, Fumero M. 2025. Connecting neural models latent geometries with relative geodesic representations. 39th Annual Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems, Advances in Neural Information Processing Systems, vol. 38.' mla: Yu, Hanlin, et al. “Connecting Neural Models Latent Geometries with Relative Geodesic Representations.” 39th Annual Conference on Neural Information Processing Systems, vol. 38, Neural Information Processing Systems Foundation, 2025. short: H. Yu, B. Inal, G. Arvanitidis, S. Hauberg, F. Locatello, M. Fumero, in:, 39th Annual Conference on Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2025. conference: end_date: 2025-12-07 location: San Diego, CA, United States name: 'NeurIPS: Neural Information Processing Systems' start_date: 2025-12-02 corr_author: '1' das_tickbox: '1' date_created: 2026-01-29T14:31:52Z date_published: 2025-12-15T00:00:00Z date_updated: 2026-07-28T07:19:01Z day: '15' ddc: - '000' department: - _id: FrLo ec_funded: 1 external_id: arxiv: - '2506.01599' file: - access_level: open_access checksum: b1a645418025f46394764cd16d0cb089 content_type: application/pdf creator: flocatel date_created: 2026-01-29T14:31:42Z date_updated: 2026-01-29T14:31:42Z file_id: '21075' file_name: 2506.01599v2.pdf file_size: 7749349 relation: main_file success: 1 file_date_updated: 2026-01-29T14:31:42Z has_accepted_license: '1' intvolume: ' 38' language: - iso: eng month: '12' oa: 1 oa_version: Published Version project: - _id: fc2ed2f7-9c52-11eb-aca3-c01059dda49c call_identifier: H2020 grant_number: '101034413' name: 'IST-BRIDGE: International postdoctoral program' publication: 39th Annual Conference on Neural Information Processing Systems publication_identifier: issn: - 1049-5258 publication_status: published publisher: Neural Information Processing Systems Foundation quality_controlled: '1' status: public title: Connecting neural models latent geometries with relative geodesic representations tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 38 year: '2025' ... --- OA_place: publisher OA_type: gold _id: '21076' abstract: - lang: eng text: In many scientific experiments, the data annotating cost constraints the pace for testing novel hypotheses. Yet, modern machine learning pipelines offer a promising solution—provided their predictions yield correct conclusions. We focus on Prediction-Powered Causal Inferences (PPCI), i.e., estimating the treatment effect in an unlabeled target experiment, relying on training data with the same outcome annotated but potentially different treatment or effect modifiers. We first show that conditional calibration guarantees valid PPCI at population level. Then, we introduce a sufficient representation constraint transferring validity across experiments, which we propose to enforce in practice in Deconfounded Empirical Risk Minimization, our new model-agnostic training objective. We validate our method on synthetic and real-world scientific data, solving impossible problem instances for Empirical Risk Minimization even with standard invariance constraints. In particular, for the first time, we achieve valid causal inference on a scientific experiment with complex recording and no human annotations, fine-tuning a foundational model on our similar annotated experiment. acknowledgement: We thank the Causal Learning and Artificial Intelligence group at ISTA for the continuous feedback on the project and valuable discussions. We thank the Social Immunity group at ISTA, particularly Jinook Oh, for the annotation program and Michaela Hoenigsberger for supporting our ecological experiment. Riccardo Cadei is supported by a Google Research Scholar Award and a Google Initiated Gift to Francesco Locatello. This research was funded in part by the Austrian Science Fund (FWF) 10.55776/COE12). It was further partially supported by the ISTA Interdisciplinary Project Committee for the collaborative project “ALED” between Francesco Locatello and Sylvia Cremer. For open access purposes, the author has applied a CC BY public copyright license to any author accepted manuscript version arising from this submission. alternative_title: - Advances in Neural Information Processing Systems article_processing_charge: No author: - first_name: Riccardo full_name: Cadei, Riccardo id: 0fa8b76f-72f0-11ef-b75a-a5da96e5ad6b last_name: Cadei - first_name: Ilker full_name: Demirel, Ilker last_name: Demirel - first_name: Piersilvio full_name: De Bartolomeis, Piersilvio last_name: De Bartolomeis - first_name: Lukas full_name: Lindorfer, Lukas id: 85f0e6d3-06b3-11ec-8982-8c5049fa4455 last_name: Lindorfer - first_name: Sylvia full_name: Cremer, Sylvia id: 2F64EC8C-F248-11E8-B48F-1D18A9856A87 last_name: Cremer orcid: 0000-0002-2193-3868 - first_name: Cordelia full_name: Schmid, Cordelia last_name: Schmid - first_name: Francesco full_name: Locatello, Francesco id: 26cfd52f-2483-11ee-8040-88983bcc06d4 last_name: Locatello orcid: 0000-0002-4850-0683 citation: ama: 'Cadei R, Demirel I, De Bartolomeis P, et al. Prediction-powered causal inferences. In: 39th Annual Conference on Neural Information Processing Systems. Vol 38. Neural Information Processing Systems Foundation; 2025.' apa: 'Cadei, R., Demirel, I., De Bartolomeis, P., Lindorfer, L., Cremer, S., Schmid, C., & Locatello, F. (2025). Prediction-powered causal inferences. In 39th Annual Conference on Neural Information Processing Systems (Vol. 38). San Diego, CA, United States: Neural Information Processing Systems Foundation.' chicago: Cadei, Riccardo, Ilker Demirel, Piersilvio De Bartolomeis, Lukas Lindorfer, Sylvia Cremer, Cordelia Schmid, and Francesco Locatello. “Prediction-Powered Causal Inferences.” In 39th Annual Conference on Neural Information Processing Systems, Vol. 38. Neural Information Processing Systems Foundation, 2025. ieee: R. Cadei et al., “Prediction-powered causal inferences,” in 39th Annual Conference on Neural Information Processing Systems, San Diego, CA, United States, 2025, vol. 38. ista: 'Cadei R, Demirel I, De Bartolomeis P, Lindorfer L, Cremer S, Schmid C, Locatello F. 2025. Prediction-powered causal inferences. 39th Annual Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems, Advances in Neural Information Processing Systems, vol. 38.' mla: Cadei, Riccardo, et al. “Prediction-Powered Causal Inferences.” 39th Annual Conference on Neural Information Processing Systems, vol. 38, Neural Information Processing Systems Foundation, 2025. short: R. Cadei, I. Demirel, P. De Bartolomeis, L. Lindorfer, S. Cremer, C. Schmid, F. Locatello, in:, 39th Annual Conference on Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2025. conference: end_date: 2025-12-07 location: San Diego, CA, United States name: 'NeurIPS: Neural Information Processing Systems' start_date: 2025-12-02 das_tickbox: '1' date_created: 2026-01-29T14:35:11Z date_published: 2025-12-15T00:00:00Z date_updated: 2026-07-28T07:20:10Z day: '15' ddc: - '000' department: - _id: FrLo - _id: SyCr file: - access_level: open_access checksum: 92467fa566cd36671a6a3b9e71ae0f71 content_type: application/pdf creator: flocatel date_created: 2026-01-29T14:35:02Z date_updated: 2026-01-29T14:35:02Z file_id: '21077' file_name: 17546_Prediction_Powered_Causa.pdf file_size: 8489023 relation: main_file success: 1 file_date_updated: 2026-01-29T14:35:02Z has_accepted_license: '1' intvolume: ' 38' language: - iso: eng month: '12' oa: 1 oa_version: Published Version publication: 39th Annual Conference on Neural Information Processing Systems publication_identifier: issn: - 1049-5258 publication_status: published publisher: Neural Information Processing Systems Foundation quality_controlled: '1' status: public title: Prediction-powered causal inferences tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 38 year: '2025' ... --- OA_place: publisher OA_type: gold _id: '21072' abstract: - lang: eng text: Language and vision-language models have shown impressive performance across a wide range of tasks, but their internal mechanisms remain only partly understood. In this work, we study how individual attention heads in text-generative models specialize in specific semantic or visual attributes. Building on an established interpretability method, we reinterpret the practice of probing intermediate activations with the final decoding layer through the lens of signal processing. This lets us analyze multiple samples in a principled way and rank attention heads based on their relevance to target concepts. Our results show consistent patterns of specialization at the head level across both unimodal and multimodal transformers. Remarkably, we find that editing as few as 1% of the heads, selected using our method, can reliably suppress or enhance targeted concepts in the model output. We validate our approach on language tasks such as question answering and toxicity mitigation, as well as vision-language tasks including image classification and captioning. Our findings highlight an interpretable and controllable structure within attention layers, offering simple tools for understanding and editing large-scale generative models. acknowledgement: 'The authors acknowledge the Area Science Park supercomputing platform ORFEO made available for conducting the research reported in this paper, and the technical support of the Laboratory of Data Engineering staff. LB, DD and AC were supported by the project “Supporto alla diagnosi di malattie rare tramite l’intelligenza artificiale" CUP: F53C22001770002 and “Valutazione automatica delle immagini diagnostiche tramite l’intelligenza artificiale", CUP: F53C22001780002. LB was supported by the European Union – NextGenerationEU within the project PNRR “Finanziamento di progetti presentati da giovani ricercatori" - Mission 4 Component 2 Investment 1.2, CUP: J93C25000440001. AC was supported by the European Union – NextGenerationEU within the project PNRR “PRP@CERIC" IR0000028 - Mission 4 Component 2 Investment 3.1 Action 3.1.1. ' article_processing_charge: No arxiv: 1 author: - first_name: Lorenzo full_name: Basile, Lorenzo last_name: Basile - first_name: Valentino full_name: Maiorca, Valentino last_name: Maiorca - first_name: Diego full_name: Doimo, Diego last_name: Doimo - first_name: Francesco full_name: Locatello, Francesco id: 26cfd52f-2483-11ee-8040-88983bcc06d4 last_name: Locatello orcid: 0000-0002-4850-0683 - first_name: Alberto full_name: Cazzaniga, Alberto last_name: Cazzaniga citation: ama: 'Basile L, Maiorca V, Doimo D, Locatello F, Cazzaniga A. Head pursuit: Probing attention specialization in multimodal transformers. In: 39th Annual Conference on Neural Information Processing Systems. Vol 38. Neural Information Processing Systems Foundation; 2025.' apa: 'Basile, L., Maiorca, V., Doimo, D., Locatello, F., & Cazzaniga, A. (2025). Head pursuit: Probing attention specialization in multimodal transformers. In 39th Annual Conference on Neural Information Processing Systems (Vol. 38). San Diego, CA, United States: Neural Information Processing Systems Foundation.' chicago: 'Basile, Lorenzo, Valentino Maiorca, Diego Doimo, Francesco Locatello, and Alberto Cazzaniga. “Head Pursuit: Probing Attention Specialization in Multimodal Transformers.” In 39th Annual Conference on Neural Information Processing Systems, Vol. 38. Neural Information Processing Systems Foundation, 2025.' ieee: 'L. Basile, V. Maiorca, D. Doimo, F. Locatello, and A. Cazzaniga, “Head pursuit: Probing attention specialization in multimodal transformers,” in 39th Annual Conference on Neural Information Processing Systems, San Diego, CA, United States, 2025, vol. 38.' ista: 'Basile L, Maiorca V, Doimo D, Locatello F, Cazzaniga A. 2025. Head pursuit: Probing attention specialization in multimodal transformers. 39th Annual Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems vol. 38.' mla: 'Basile, Lorenzo, et al. “Head Pursuit: Probing Attention Specialization in Multimodal Transformers.” 39th Annual Conference on Neural Information Processing Systems, vol. 38, Neural Information Processing Systems Foundation, 2025.' short: L. Basile, V. Maiorca, D. Doimo, F. Locatello, A. Cazzaniga, in:, 39th Annual Conference on Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2025. conference: end_date: 2025-12-07 location: San Diego, CA, United States name: 'NeurIPS: Neural Information Processing Systems' start_date: 2025-12-02 das_tickbox: '1' date_created: 2026-01-29T14:29:23Z date_published: 2025-12-15T00:00:00Z date_updated: 2026-07-28T07:18:12Z day: '15' ddc: - '000' department: - _id: FrLo external_id: arxiv: - '2510.21518' file: - access_level: open_access checksum: 85be3f98663e2595cf37001852b477cb content_type: application/pdf creator: flocatel date_created: 2026-01-29T14:29:14Z date_updated: 2026-01-29T14:29:14Z file_id: '21073' file_name: 2510.21518v2.pdf file_size: 4271547 relation: main_file success: 1 file_date_updated: 2026-01-29T14:29:14Z has_accepted_license: '1' intvolume: ' 38' language: - iso: eng month: '12' oa: 1 oa_version: Preprint publication: 39th Annual Conference on Neural Information Processing Systems publication_identifier: issn: - 1049-5258 publication_status: published publisher: Neural Information Processing Systems Foundation quality_controlled: '1' status: public title: 'Head pursuit: Probing attention specialization in multimodal transformers' tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 38 year: '2025' ... --- OA_place: repository OA_type: green _id: '21068' abstract: - lang: eng text: "Causal reasoning and discovery, two fundamental tasks of causal analysis,\r\noften face challenges in applications due to the complexity, noisiness, and highdimensionality of real-world data. Despite recent progress in identifying latent\r\ncausal structures using causal representation learning (CRL), what makes learned\r\nrepresentations useful for causal downstream tasks and how to evaluate them are\r\nstill not well understood. In this paper, we reinterpret CRL using a measurement\r\nmodel framework, where the learned representations are viewed as proxy measurements of the latent causal variables. Our approach clarifies the conditions under\r\nwhich learned representations support downstream causal reasoning and provides\r\na principled basis for quantitatively assessing the quality of representations using\r\na new Test-based Measurement EXclusivity (T-MEX) score. We validate T-MEX\r\nacross diverse causal inference scenarios, including numerical simulations and\r\nreal-world ecological video analysis, demonstrating that the proposed framework\r\nand corresponding score effectively assess the identification of learned representations and their usefulness for causal downstream tasks. Reproducible code can\r\nbe found at https://github.com/shimenghuang/a-measurement-perspective-of-crl." acknowledgement: "This research was funded in whole or in part by the Austrian Science Fund (FWF) 10.55776/COE12. For open access purposes, the author has applied a CC BY public copyright license to any accepted manuscript version arising from this submission.\r\n" alternative_title: - Advances in Neural Information Processing Systems article_processing_charge: No arxiv: 1 author: - first_name: Dingling full_name: Yao, Dingling id: d3e02e50-48a8-11ee-8f62-c108061797fa last_name: Yao - first_name: Shimeng full_name: Huang, Shimeng id: 989c2a06-fb4e-11ef-a992-ab766442255b last_name: Huang orcid: 0000-0001-6919-821X - first_name: Riccardo full_name: Cadei, Riccardo id: 0fa8b76f-72f0-11ef-b75a-a5da96e5ad6b last_name: Cadei - first_name: Kun full_name: Zhang, Kun last_name: Zhang - first_name: Francesco full_name: Locatello, Francesco id: 26cfd52f-2483-11ee-8040-88983bcc06d4 last_name: Locatello orcid: 0000-0002-4850-0683 citation: ama: 'Yao D, Huang S, Cadei R, Zhang K, Locatello F. The third pillar of causal analysis? A measurement perspective on causal representations. In: 39th Annual Conference on Neural Information Processing Systems. Vol 38. Neural Information Processing Systems Foundation; 2025.' apa: 'Yao, D., Huang, S., Cadei, R., Zhang, K., & Locatello, F. (2025). The third pillar of causal analysis? A measurement perspective on causal representations. In 39th Annual Conference on Neural Information Processing Systems (Vol. 38). San Diego, CA, United States: Neural Information Processing Systems Foundation.' chicago: Yao, Dingling, Shimeng Huang, Riccardo Cadei, Kun Zhang, and Francesco Locatello. “The Third Pillar of Causal Analysis? A Measurement Perspective on Causal Representations.” In 39th Annual Conference on Neural Information Processing Systems, Vol. 38. Neural Information Processing Systems Foundation, 2025. ieee: D. Yao, S. Huang, R. Cadei, K. Zhang, and F. Locatello, “The third pillar of causal analysis? A measurement perspective on causal representations,” in 39th Annual Conference on Neural Information Processing Systems, San Diego, CA, United States, 2025, vol. 38. ista: 'Yao D, Huang S, Cadei R, Zhang K, Locatello F. 2025. The third pillar of causal analysis? A measurement perspective on causal representations. 39th Annual Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems, Advances in Neural Information Processing Systems, vol. 38.' mla: Yao, Dingling, et al. “The Third Pillar of Causal Analysis? A Measurement Perspective on Causal Representations.” 39th Annual Conference on Neural Information Processing Systems, vol. 38, Neural Information Processing Systems Foundation, 2025. short: D. Yao, S. Huang, R. Cadei, K. Zhang, F. Locatello, in:, 39th Annual Conference on Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2025. conference: end_date: 2025-12-07 location: San Diego, CA, United States name: 'NeurIPS: Neural Information Processing Systems' start_date: 2025-12-02 corr_author: '1' das_tickbox: '1' date_created: 2026-01-29T14:24:56Z date_published: 2025-12-15T00:00:00Z date_updated: 2026-07-28T07:14:27Z day: '15' ddc: - '000' department: - _id: FrLo external_id: arxiv: - '2505.17708' has_accepted_license: '1' intvolume: ' 38' language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.48550/arXiv.2505.17708 month: '12' oa: 1 oa_version: Preprint publication: 39th Annual Conference on Neural Information Processing Systems publication_identifier: issn: - 1049-5258 publication_status: published publisher: Neural Information Processing Systems Foundation quality_controlled: '1' related_material: link: - relation: software url: https://github.com/shimenghuang/a-measurement-perspective-of-crl status: public title: The third pillar of causal analysis? A measurement perspective on causal representations tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 38 year: '2025' ... --- OA_place: repository OA_type: green _id: '21070' abstract: - lang: eng text: 'Deep learning systems deployed in real-world applications often encounter data that is different from their in-distribution (ID). A reliable model should ideally abstain from making decisions in this out-of-distribution (OOD) setting. Existing state-of-the-art methods primarily focus on feature distances, such as k-th nearest neighbors and distances to decision boundaries, either overlooking or ineffectively using in-distribution statistics. In this work, we propose a novel angle-based metric for OOD detection that is computed relative to the in-distribution structure. We demonstrate that the angles between feature representations and decision boundaries, viewed from the mean of in-distribution features, serve as an effective discriminative factor between ID and OOD data. We evaluate our method on nine ImageNet-pretrained models. Our approach achieves the lowest FPR in 5 out of 9 ImageNet models, obtains the best average FPR overall, and consistently ranking among the top 3 across all evaluated models. Furthermore, we highlight the benefits of contrastive representations by showing strong performance with ResNet SCL and CLIP architectures. Finally, we demonstrate that the scale-invariant nature of our score enables an ensemble strategy via simple score summation. ' acknowledgement: "This research was funded in whole or in part by the Austrian Science Fund (FWF) 10.55776/COE12. For open access purposes, the author has applied a CC BY public copyright license to any accepted manuscript version arising from this submission.\r\n" alternative_title: - Advances in Neural Information Processing Systems article_processing_charge: No arxiv: 1 author: - first_name: Berker full_name: Demirel, Berker id: 8b4bc47f-3200-11ee-973b-8f0e7be21a9f last_name: Demirel - first_name: 'Marco ' full_name: 'Fumero, Marco ' last_name: Fumero - first_name: Francesco full_name: Locatello, Francesco id: 26cfd52f-2483-11ee-8040-88983bcc06d4 last_name: Locatello orcid: 0000-0002-4850-0683 citation: ama: 'Demirel B, Fumero M, Locatello F. Out-of-Distribution detection with relative angles. In: 39th Annual Conference on Neural Information Processing Systems. Vol 38. Neural Information Processing Systems Foundation; 2025.' apa: 'Demirel, B., Fumero, M., & Locatello, F. (2025). Out-of-Distribution detection with relative angles. In 39th Annual Conference on Neural Information Processing Systems (Vol. 38). San Diego, CA, United States: Neural Information Processing Systems Foundation.' chicago: Demirel, Berker, Marco Fumero, and Francesco Locatello. “Out-of-Distribution Detection with Relative Angles.” In 39th Annual Conference on Neural Information Processing Systems, Vol. 38. Neural Information Processing Systems Foundation, 2025. ieee: B. Demirel, M. Fumero, and F. Locatello, “Out-of-Distribution detection with relative angles,” in 39th Annual Conference on Neural Information Processing Systems, San Diego, CA, United States, 2025, vol. 38. ista: 'Demirel B, Fumero M, Locatello F. 2025. Out-of-Distribution detection with relative angles. 39th Annual Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems, Advances in Neural Information Processing Systems, vol. 38.' mla: Demirel, Berker, et al. “Out-of-Distribution Detection with Relative Angles.” 39th Annual Conference on Neural Information Processing Systems, vol. 38, Neural Information Processing Systems Foundation, 2025. short: B. Demirel, M. Fumero, F. Locatello, in:, 39th Annual Conference on Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2025. conference: end_date: 2025-12-07 location: San Diego, CA, United States name: 'NeurIPS: Neural Information Processing Systems' start_date: 2025-12-02 corr_author: '1' das_tickbox: '1' date_created: 2026-01-29T14:26:47Z date_published: 2025-12-01T00:00:00Z date_updated: 2026-07-28T07:15:44Z day: '01' ddc: - '000' department: - _id: FrLo external_id: arxiv: - '2410.04525' has_accepted_license: '1' intvolume: ' 38' language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.48550/arXiv.2410.04525 month: '12' oa: 1 oa_version: Preprint publication: 39th Annual Conference on Neural Information Processing Systems publication_identifier: issn: - 1049-5258 publication_status: published publisher: Neural Information Processing Systems Foundation quality_controlled: '1' related_material: link: - relation: software url: https://github.com/berkerdemirel/ORA-OOD-Detection-with-Relative-Angles status: public title: Out-of-Distribution detection with relative angles tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 38 year: '2025' ... --- OA_place: publisher OA_type: hybrid PlanS_conform: '1' _id: '20326' abstract: - lang: eng text: Ag2Se is a promising n-type thermoelectric material, but its performance is limited by excessive carrier concentration, compositional inhomogeneity, and phase instability, challenges rooted in a narrow homogeneity range and uncontrolled Ag+ diffusion in the superionic phase. Here, we address these issues by exploiting liquid–solid interface reactions using CdSe complexes that remove surface excess Ag to yield stoichiometric Ag2Se and generate CdSe nanodomains that inhibit Ag+ diffusion and constrain grain growth. The resulting Ag2Se-CdSe nanocomposites exhibit a reproducible, stable figure of merit (zT) of 1.04 between 300 and 390 K. Beyond demonstrating high performance, we elucidate the interfacial chemical reactions that give rise to the observed microstructure and transport properties, providing a foundation for rationally engineering interfacial chemistry to tailor transport properties across diverse thermoelectric material systems. acknowledged_ssus: - _id: EM-Fac - _id: LifeSc - _id: NanoFab - _id: MassSpec acknowledgement: 'M.I. acknowledges financial support from ISTA and the Werner Siemens Foundation. The Scientific Service Units (SSU) of ISTA supported this work through resources provided by the Electron Microscopy Facility (EMF), the Lab Support Facility (LSF) and the Nanofabrication Facility (NNF) and the LSF Mass Spectrometry Service. The members of the Ibáñez research group are acknowledged, especially Christine Fiedler for scientific illustration and Ihor Cherniukh for valuable discussions. Y.L. acknowledges funding from the National Natural Science Foundation of China (NSFC) (Grants No. 22209034), the Innovation and Entrepreneurship Project of Overseas Returnees in Anhui Province (Grant No. 2022LCX002) and the Fundamental Research Funds for the Central Universities (JZ2024HGTB0239). K.H.L. acknowledges financial support from the National Natural Science Foundation of China (NSFC) (Grant No. 22208293). ICN2 acknowledges funding from Generalitat de Catalunya 2021SGR00457. Authors acknowledge the Advanced Materials programme by the Spanish Government with funding from European Union NextGenerationEU (PRTR-C17.I1) and by Generalitat de Catalunya (Project In-CAEM). The authors thank support from the project AMaDE (PID2023-149158OB-C43), funded by MCIN/AEI/10.13039/501100011033/and by “ERDF Away of making Europe”, by the “European Union”. ICN2 is supported by the Severo Ochoa program from Spanish MCIN/AEI (Grant No.: CEX2021-001214-S) and is funded by the CERCA Programme/Generalitat de Catalunya. ICN2 is founding member of e-DREAM. (68) M.H. acknowledges the funding from the Australian Research Council (FT230100316 and IH200100035). M.H. acknowledges the computational support from the National Computational Infrastructure (NCI) and Pawsey Supercomputing Centre, Australia.' article_processing_charge: Yes (via OA deal) article_type: original author: - first_name: Yu full_name: Liu, Yu id: 2A70014E-F248-11E8-B48F-1D18A9856A87 last_name: Liu orcid: 0000-0001-7313-6740 - first_name: Tobias full_name: Kleinhanns, Tobias id: 8BD9DE16-AB3C-11E9-9C8C-2A03E6697425 last_name: Kleinhanns orcid: 0000-0003-1537-7436 - first_name: Sharona full_name: Horta, Sharona id: 03a7e858-01b1-11ec-8b71-99ae6c4a05bc last_name: Horta - first_name: Ewelina full_name: Dutkiewicz, Ewelina id: 0601cc46-c082-11ec-9b07-bb29641d1de9 last_name: Dutkiewicz - first_name: Shaoqing full_name: Lu, Shaoqing last_name: Lu - first_name: Maria Chiara full_name: Spadaro, Maria Chiara last_name: Spadaro - first_name: Aziz full_name: Genç, Aziz last_name: Genç - first_name: Lei full_name: Chen, Lei last_name: Chen - first_name: Khak Ho full_name: Lim, Khak Ho last_name: Lim - first_name: Min full_name: Hong, Min last_name: Hong - first_name: Jordi full_name: Arbiol, Jordi last_name: Arbiol - first_name: Maria full_name: Ibáñez, Maria id: 43C61214-F248-11E8-B48F-1D18A9856A87 last_name: Ibáñez orcid: 0000-0001-5013-2843 citation: ama: Liu Y, Kleinhanns T, Horta S, et al. Liquid-solid interface reactions drive enhanced thermoelectric performance in Ag2Se. Journal of the American Chemical Society. 2025;147(35):32199-32208. doi:10.1021/jacs.5c11435 apa: Liu, Y., Kleinhanns, T., Horta, S., Dutkiewicz, E., Lu, S., Spadaro, M. C., … Ibáñez, M. (2025). Liquid-solid interface reactions drive enhanced thermoelectric performance in Ag2Se. Journal of the American Chemical Society. American Chemical Society. https://doi.org/10.1021/jacs.5c11435 chicago: Liu, Yu, Tobias Kleinhanns, Sharona Horta, Ewelina Dutkiewicz, Shaoqing Lu, Maria Chiara Spadaro, Aziz Genç, et al. “Liquid-Solid Interface Reactions Drive Enhanced Thermoelectric Performance in Ag2Se.” Journal of the American Chemical Society. American Chemical Society, 2025. https://doi.org/10.1021/jacs.5c11435. ieee: Y. Liu et al., “Liquid-solid interface reactions drive enhanced thermoelectric performance in Ag2Se,” Journal of the American Chemical Society, vol. 147, no. 35. American Chemical Society, pp. 32199–32208, 2025. ista: Liu Y, Kleinhanns T, Horta S, Dutkiewicz E, Lu S, Spadaro MC, Genç A, Chen L, Lim KH, Hong M, Arbiol J, Ibáñez M. 2025. Liquid-solid interface reactions drive enhanced thermoelectric performance in Ag2Se. Journal of the American Chemical Society. 147(35), 32199–32208. mla: Liu, Yu, et al. “Liquid-Solid Interface Reactions Drive Enhanced Thermoelectric Performance in Ag2Se.” Journal of the American Chemical Society, vol. 147, no. 35, American Chemical Society, 2025, pp. 32199–208, doi:10.1021/jacs.5c11435. short: Y. Liu, T. Kleinhanns, S. Horta, E. Dutkiewicz, S. Lu, M.C. Spadaro, A. Genç, L. Chen, K.H. Lim, M. Hong, J. Arbiol, M. Ibáñez, Journal of the American Chemical Society 147 (2025) 32199–32208. corr_author: '1' date_created: 2025-09-10T05:44:03Z date_published: 2025-08-22T00:00:00Z date_updated: 2026-07-28T09:55:14Z day: '22' ddc: - '540' department: - _id: MaIb - _id: MassSpec doi: 10.1021/jacs.5c11435 external_id: isi: - '001558320100001' file: - access_level: open_access checksum: 52892fa91adadd39a1c42da9e01139a5 content_type: application/pdf creator: dernst date_created: 2025-09-10T06:55:17Z date_updated: 2025-09-10T06:55:17Z file_id: '20334' file_name: 2025_JACS_Liu.pdf file_size: 9997327 relation: main_file success: 1 file_date_updated: 2025-09-10T06:55:17Z has_accepted_license: '1' intvolume: ' 147' isi: 1 issue: '35' language: - iso: eng month: '08' oa: 1 oa_version: Published Version page: 32199-32208 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: Journal of the American Chemical Society publication_identifier: eissn: - 1520-5126 issn: - 0002-7863 publication_status: published publisher: American Chemical Society quality_controlled: '1' related_material: record: - id: '22017' relation: dissertation_contains status: public scopus_import: '1' status: public title: Liquid-solid interface reactions drive enhanced thermoelectric performance in Ag2Se 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: 147 year: '2025' ...