--- OA_place: publisher OA_type: hybrid _id: '10045' abstract: - lang: eng text: "Given a fixed finite metric space (V,μ), the {\\em minimum 0-extension problem}, denoted as 0-Ext[μ], is equivalent to the following optimization problem: minimize function of the form minx∈Vn∑ifi(xi)+∑ijcijμ(xi,xj) where cij,cvi are given nonnegative costs and fi:V→R are functions given by fi(xi)=∑v∈Vcviμ(xi,v). The computational complexity of 0-Ext[μ] has been recently established by Karzanov and by Hirai: if metric μ is {\\em orientable modular} then 0-Ext[μ] can be solved in polynomial time, otherwise 0-Ext[μ] is NP-hard. To prove the tractability part, Hirai developed a theory of discrete convex functions on orientable modular graphs generalizing several known classes of functions in discrete convex analysis, such as L♮-convex functions. We consider a more general version of the problem in which unary functions fi(xi) can additionally have terms of the form cuv;iμ(xi,{u,v}) for {u,v}∈F, where set F⊆(V2) is fixed. We extend the complexity classification above by providing an explicit condition on (μ,F) for the problem to be tractable. In order to prove the tractability part, we generalize Hirai's theory and define a larger class of discrete convex functions. It covers, in particular, another well-known class of functions, namely submodular functions on an integer lattice. Finally, we improve the complexity of Hirai's algorithm for solving 0-Ext on orientable modular graphs.\r\n" acknowledgement: We thank the anonymous reviewers for their careful reading of our manuscript and their many insightful comments and suggestions. Open access funding provided by Institute of Science and Technology (IST Austria). article_processing_charge: Yes (via OA deal) article_type: original arxiv: 1 author: - first_name: Martin full_name: Dvorak, Martin id: 40ED02A8-C8B4-11E9-A9C0-453BE6697425 last_name: Dvorak orcid: 0000-0001-5293-214X - first_name: Vladimir full_name: Kolmogorov, Vladimir id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87 last_name: Kolmogorov citation: ama: Dvorak M, Kolmogorov V. Generalized minimum 0-extension problem and discrete convexity. Mathematical Programming. 2025;209:279-322. doi:10.1007/s10107-024-02064-5 apa: Dvorak, M., & Kolmogorov, V. (2025). Generalized minimum 0-extension problem and discrete convexity. Mathematical Programming. Springer Nature. https://doi.org/10.1007/s10107-024-02064-5 chicago: Dvorak, Martin, and Vladimir Kolmogorov. “Generalized Minimum 0-Extension Problem and Discrete Convexity.” Mathematical Programming. Springer Nature, 2025. https://doi.org/10.1007/s10107-024-02064-5. ieee: M. Dvorak and V. Kolmogorov, “Generalized minimum 0-extension problem and discrete convexity,” Mathematical Programming, vol. 209. Springer Nature, pp. 279–322, 2025. ista: Dvorak M, Kolmogorov V. 2025. Generalized minimum 0-extension problem and discrete convexity. Mathematical Programming. 209, 279–322. mla: Dvorak, Martin, and Vladimir Kolmogorov. “Generalized Minimum 0-Extension Problem and Discrete Convexity.” Mathematical Programming, vol. 209, Springer Nature, 2025, pp. 279–322, doi:10.1007/s10107-024-02064-5. short: M. Dvorak, V. Kolmogorov, Mathematical Programming 209 (2025) 279–322. corr_author: '1' das_tickbox: '0' date_created: 2021-09-27T10:48:23Z date_published: 2025-01-01T00:00:00Z date_updated: 2026-10-02T11:45:16Z day: '01' ddc: - '004' department: - _id: GradSch - _id: VlKo doi: 10.1007/s10107-024-02064-5 external_id: arxiv: - '2109.10203' isi: - '001176563300001' file: - access_level: open_access checksum: 25d9bd490719b45eca84f4d93a06c69f content_type: application/pdf creator: dernst date_created: 2025-04-16T09:36:08Z date_updated: 2025-04-16T09:36:08Z file_id: '19578' file_name: 2025_MathProgramming_Dvorak.pdf file_size: 839510 relation: main_file success: 1 file_date_updated: 2025-04-16T09:36:08Z fulldoi: https://doi.org/10.1007/s10107-024-02064-5 has_accepted_license: '1' intvolume: ' 209' isi: 1 keyword: - minimum 0-extension problem - metric labeling problem - discrete metric spaces - metric extensions - computational complexity - valued constraint satisfaction problems - discrete convex analysis - L-convex functions language: - iso: eng month: '01' oa: 1 oa_version: Published Version page: 279-322 publication: Mathematical Programming publication_identifier: eissn: - 1436-4646 issn: - 0025-5610 publication_status: published publisher: Springer Nature quality_controlled: '1' researchdata_availability: no scopus_import: '1' status: public supplementarymaterial: no title: Generalized minimum 0-extension problem and discrete convexity tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345 volume: 209 year: '2025' ... --- OA_place: publisher OA_type: hybrid _id: '17149' abstract: - lang: eng text: The approximation of a circle with the edges of a fine square grid distorts the perimeter by a factor about 4/Pi. We prove that this factor is the same on average (in the ergodic sense) for approximations of any rectifiable curve by the edges of any non-exotic Delaunay mosaic (known as Voronoi path), and extend the results to all dimensions, generalizing Voronoi paths to Voronoi scapes. acknowledgement: "The authors thank Ranita Biswas and Tatiana Ezubova for the collaboration on computational experiments that motivated the work reported in this paper. The authors also thank Daniel Bonnema for proofreading and noticing an issue with the original proof of Lemma 4.3.\r\nOpen access funding provided by Institute of Science and Technology (IST Austria).\r\nThis project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme, Grant No. 788183, from the Wittgenstein Prize, Austrian Science Fund (FWF), Grant No. Z 342-N31, and from the DFG Collaborative Research Center TRR 109, ‘Discretization in Geometry and Dynamics’, Austrian Science Fund (FWF), Grant No. I 02979-N35." article_processing_charge: Yes (via OA deal) article_type: original 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: Anton full_name: Nikitenko, Anton id: 3E4FF1BA-F248-11E8-B48F-1D18A9856A87 last_name: Nikitenko orcid: 0000-0002-0659-3201 citation: ama: Edelsbrunner H, Nikitenko A. Average and expected distortion of Voronoi paths and scapes. Discrete & Computational Geometry. 2025;73:490-499. doi:10.1007/s00454-024-00660-y apa: Edelsbrunner, H., & Nikitenko, A. (2025). Average and expected distortion of Voronoi paths and scapes. Discrete & Computational Geometry. Springer Nature. https://doi.org/10.1007/s00454-024-00660-y chicago: Edelsbrunner, Herbert, and Anton Nikitenko. “Average and Expected Distortion of Voronoi Paths and Scapes.” Discrete & Computational Geometry. Springer Nature, 2025. https://doi.org/10.1007/s00454-024-00660-y. ieee: H. Edelsbrunner and A. Nikitenko, “Average and expected distortion of Voronoi paths and scapes,” Discrete & Computational Geometry, vol. 73. Springer Nature, pp. 490–499, 2025. ista: Edelsbrunner H, Nikitenko A. 2025. Average and expected distortion of Voronoi paths and scapes. Discrete & Computational Geometry. 73, 490–499. mla: Edelsbrunner, Herbert, and Anton Nikitenko. “Average and Expected Distortion of Voronoi Paths and Scapes.” Discrete & Computational Geometry, vol. 73, Springer Nature, 2025, pp. 490–99, doi:10.1007/s00454-024-00660-y. short: H. Edelsbrunner, A. Nikitenko, Discrete & Computational Geometry 73 (2025) 490–499. corr_author: '1' das_tickbox: '0' date_created: 2024-06-16T22:01:07Z date_published: 2025-03-01T00:00:00Z date_updated: 2026-10-02T11:48:46Z day: '01' ddc: - '510' department: - _id: HeEd doi: 10.1007/s00454-024-00660-y ec_funded: 1 external_id: arxiv: - '2012.03350' isi: - '001238566200004' pmid: - '39974750' file: - access_level: open_access checksum: ffb0c818222138f9f113f4bbea41e834 content_type: application/pdf creator: dernst date_created: 2025-04-23T07:31:32Z date_updated: 2025-04-23T07:31:32Z file_id: '19610' file_name: 2025_DiscreteComputGeom_EdelsbrunnerHe.pdf file_size: 283443 relation: main_file success: 1 file_date_updated: 2025-04-23T07:31:32Z fulldoi: https://doi.org/10.1007/s00454-024-00660-y has_accepted_license: '1' intvolume: ' 73' isi: 1 language: - iso: eng month: '03' oa: 1 oa_version: Published Version page: 490-499 pmid: 1 project: - _id: 266A2E9E-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '788183' name: Alpha Shape Theory Extended - _id: 268116B8-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z00342 name: Mathematics, Computer Science - _id: 2561EBF4-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: I02979-N35 name: Persistence and stability of geometric complexes publication: Discrete & Computational Geometry publication_identifier: eissn: - 1432-0444 issn: - 0179-5376 publication_status: published publisher: Springer Nature quality_controlled: '1' researchdata_availability: no scopus_import: '1' status: public supplementarymaterial: no title: Average and expected distortion of Voronoi paths and scapes tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345 volume: 73 year: '2025' ... --- OA_place: repository OA_type: green _id: '21253' abstract: - lang: eng text: We solve a problem of Dujmović and Wood (2007) by showing that a complete convex geometric graph on n vertices cannot be decomposed into fewer than n - 1 star-forests, each consisting of noncrossing edges. This bound is clearly tight. We also discuss similar questions for abstract graphs. acknowledgement: A preliminary version of this note has been published in the proceedings of the 31st International Symposium on Graph Drawing and Network Visualization, Palermo, 2023. The authors would like to thank the anonymous referees for their valuable comments. article_number: '102186' article_processing_charge: No article_type: original arxiv: 1 author: - first_name: János full_name: Pach, János last_name: Pach - first_name: Morteza full_name: Saghafian, Morteza id: f86f7148-b140-11ec-9577-95435b8df824 last_name: Saghafian - first_name: Patrick full_name: Schnider, Patrick last_name: Schnider citation: ama: Pach J, Saghafian M, Schnider P. Decomposition of geometric graphs into star-forests. Computational Geometry. 2025;129. doi:10.1016/j.comgeo.2025.102186 apa: Pach, J., Saghafian, M., & Schnider, P. (2025). Decomposition of geometric graphs into star-forests. Computational Geometry. Elsevier. https://doi.org/10.1016/j.comgeo.2025.102186 chicago: Pach, János, Morteza Saghafian, and Patrick Schnider. “Decomposition of Geometric Graphs into Star-Forests.” Computational Geometry. Elsevier, 2025. https://doi.org/10.1016/j.comgeo.2025.102186. ieee: J. Pach, M. Saghafian, and P. Schnider, “Decomposition of geometric graphs into star-forests,” Computational Geometry, vol. 129. Elsevier, 2025. ista: Pach J, Saghafian M, Schnider P. 2025. Decomposition of geometric graphs into star-forests. Computational Geometry. 129, 102186. mla: Pach, János, et al. “Decomposition of Geometric Graphs into Star-Forests.” Computational Geometry, vol. 129, 102186, Elsevier, 2025, doi:10.1016/j.comgeo.2025.102186. short: J. Pach, M. Saghafian, P. Schnider, Computational Geometry 129 (2025). corr_author: '1' date_created: 2026-02-16T15:48:42Z date_published: 2025-12-01T00:00:00Z date_updated: 2026-10-02T11:50:58Z day: '01' department: - _id: HeEd doi: 10.1016/j.comgeo.2025.102186 external_id: arxiv: - '2306.13201' fulldoi: https://doi.org/10.1016/j.comgeo.2025.102186 intvolume: ' 129' language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.48550/arXiv.2306.13201 month: '12' oa: 1 oa_version: Preprint publication: Computational Geometry publication_identifier: issn: - 0925-7721 publication_status: published publisher: Elsevier quality_controlled: '1' related_material: record: - id: '15012' relation: earlier_version status: public status: public title: Decomposition of geometric graphs into star-forests type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 129 year: '2025' ... --- OA_place: publisher _id: '18979' abstract: - lang: eng text: "Topological Data Analysis (TDA) is a discipline utilizing the mathematical field of topology to study data, most prominently collections of point sets. This thesis summarizes three projects related to computations in TDA.\r\n\r\nThe first one establishes a variant of TDA for chromatic point sets, where each point is given a color. For example, we are given positions of cells within a tumor microenvironment, and color the cancerous cells red, and the immune cells blue.\r\n\r\nThe aim is then to give a quantitative description of how the two or more sets of points spatially interact. Building on image, kernel and cokernel variants of persistent homology, we suggest six-packs of persistent diagrams as such a descriptor.\r\n\r\nWe describe a construction of a chromatic alpha complex, which enables efficient computation of several variants of the six-packs. We give topological descriptions of natural subcomplexes of the chromatic alpha complex, and show that the radii of the simplices form a discrete Morse function. Finally, we provide an implementation of the presented chromatic TDA pipeline.\r\n\r\nThe second part aims to translate a powerful tool of sheaf theory to elementary terms using labeled matrices. The goal is to enable their use in computational settings. We show that derived categories of sheaves over finite posets have, up to isomorphism, unique objects---minimal injective resolutions---and give a concrete algorithm to compute them. We further describe simple algorithms to compute derived pushforwards and pullbacks for monotonic maps, and their proper variants for inclusions, and demonstrate their tractability by providing an implementation. Finally, we suggest a discrete definition of microsupport and show desirable properties inspired by discrete Morse theory.\r\n\r\nIn the last part, we present a collection of observations about collapses. We give a characterization of collapsibility in terms of unitriangular submatrices of the boundary matrix, a cotree-tree decomposition, and the optimal solution to a variant of the Procrustes problem. We establish relation between dual collapses and relative Morse theory and pose several open questions. Finally, focusing on complexes embedded in the three-dimensional Euclidean space, we describe a relation between the collapsibility and the triviality of a polygonal knot." acknowledgement: "The research presented in this thesis was funded with the Wittgenstein Prize,\r\nAustrian Science Fund (FWF), grant no. Z 342-N31, and from the DFG Collaborative Research\r\nCenter TRR 109, ‘Discretization in Geometry and Dynamics’, Austrian Science Fund (FWF),\r\ngrant no. I 02979-N35.\r\n" alternative_title: - ISTA Thesis article_processing_charge: No author: - first_name: Ondrej full_name: Draganov, Ondrej id: 2B23F01E-F248-11E8-B48F-1D18A9856A87 last_name: Draganov orcid: 0000-0003-0464-3823 citation: ama: Draganov O. Structures and computations in topological data analysis. 2025. doi:10.15479/at:ista:18979 apa: Draganov, O. (2025). Structures and computations in topological data analysis. Institute of Science and Technology Austria. https://doi.org/10.15479/at:ista:18979 chicago: Draganov, Ondrej. “Structures and Computations in Topological Data Analysis.” Institute of Science and Technology Austria, 2025. https://doi.org/10.15479/at:ista:18979. ieee: O. Draganov, “Structures and computations in topological data analysis,” Institute of Science and Technology Austria, 2025. ista: Draganov O. 2025. Structures and computations in topological data analysis. Institute of Science and Technology Austria. mla: Draganov, Ondrej. Structures and Computations in Topological Data Analysis. Institute of Science and Technology Austria, 2025, doi:10.15479/at:ista:18979. short: O. Draganov, Structures and Computations in Topological Data Analysis, Institute of Science and Technology Austria, 2025. corr_author: '1' date_created: 2025-01-31T17:04:40Z date_published: 2025-02-03T00:00:00Z date_updated: 2026-10-02T11:57:00Z day: '03' ddc: - '514' - '004' degree_awarded: PhD department: - _id: GradSch - _id: HeEd doi: 10.15479/at:ista:18979 file: - access_level: closed checksum: af6567e5d35e5eb330b8925ae37f1998 content_type: application/zip creator: odragano date_created: 2025-01-31T16:58:30Z date_updated: 2025-01-31T16:58:30Z file_id: '18983' file_name: Thesis.zip file_size: 11899491 relation: source_file - access_level: open_access checksum: c3fef68e35b9dc2020b2ca6006da6343 content_type: application/pdf creator: odragano date_created: 2025-02-04T16:22:07Z date_updated: 2025-02-04T16:22:07Z file_id: '19000' file_name: Thesis.pdf file_size: 8857514 relation: main_file file_date_updated: 2025-02-04T16:22:07Z fulldoi: https://doi.org/10.15479/at:ista:18979 has_accepted_license: '1' keyword: - topological data analysis - chromatic point set - alpha complex - persistent homology - six pack - sheaf - microlocal discrete Morse - injective resolution - collapse - knot - discrete Morse theory language: - iso: eng month: '02' oa: 1 oa_version: Published Version page: '140' project: - _id: 2561EBF4-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: I02979-N35 name: Persistence and stability of geometric complexes - _id: 268116B8-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z00342 name: Mathematics, Computer Science publication_identifier: issn: - 2663-337X publication_status: published publisher: Institute of Science and Technology Austria related_material: record: - id: '15091' relation: part_of_dissertation status: public - id: '18981' relation: part_of_dissertation status: public status: public supervisor: - first_name: Herbert full_name: Edelsbrunner, Herbert id: 3FB178DA-F248-11E8-B48F-1D18A9856A87 last_name: Edelsbrunner orcid: 0000-0002-9823-6833 title: Structures and computations in topological data analysis 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: dissertation user_id: ba8df636-2132-11f1-aed0-ed93e2281fdd year: '2025' ... --- OA_place: publisher OA_type: hybrid PlanS_conform: '1' _id: '20323' abstract: - lang: eng text: We establish several results combining discrete Morse theory and microlocal sheaf theory in the setting of finite posets and simplicial complexes. Our primary tool is a computationally tractable description of the bounded derived category of sheaves on a poset with the Alexandrov topology. We prove that each bounded complex of sheaves on a finite poset admits a unique (up to isomorphism of complexes) minimal injective resolution, and we provide algorithms for computing minimal injective resolution of an injective complex, as well as several useful functors between derived categories of sheaves. For the constant sheaf on a simplicial complex, we give asymptotically tight bounds on the complexity of computing the minimal injective resolution using those algorithms. Our main result is a novel definition of the discrete microsupport of a bounded complex of sheaves on a finite poset. We detail several foundational properties of the discrete microsupport, as well as a microlocal generalization of the discrete homological Morse theorem and Morse inequalities. acknowledgement: This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme, grant no. 788183, from the Wittgenstein Prize, Austrian Science Fund (FWF), grant no. Z342-N31, and from the DFG Collaborative Research Center TRR 109, ‘Discretization in Geometry and Dynamics’, Austrian Science Fund (FWF), grant no. I 02979-N35 article_number: '108068' article_processing_charge: Yes (via OA deal) article_type: original arxiv: 1 author: - first_name: Adam full_name: Brown, Adam id: 70B7FDF6-608D-11E9-9333-8535E6697425 last_name: Brown - first_name: Ondrej full_name: Draganov, Ondrej id: 2B23F01E-F248-11E8-B48F-1D18A9856A87 last_name: Draganov orcid: 0000-0003-0464-3823 citation: ama: Brown A, Draganov O. Discrete microlocal Morse theory. Journal of Pure and Applied Algebra. 2025;229(10). doi:10.1016/j.jpaa.2025.108068 apa: Brown, A., & Draganov, O. (2025). Discrete microlocal Morse theory. Journal of Pure and Applied Algebra. Elsevier. https://doi.org/10.1016/j.jpaa.2025.108068 chicago: Brown, Adam, and Ondrej Draganov. “Discrete Microlocal Morse Theory.” Journal of Pure and Applied Algebra. Elsevier, 2025. https://doi.org/10.1016/j.jpaa.2025.108068. ieee: A. Brown and O. Draganov, “Discrete microlocal Morse theory,” Journal of Pure and Applied Algebra, vol. 229, no. 10. Elsevier, 2025. ista: Brown A, Draganov O. 2025. Discrete microlocal Morse theory. Journal of Pure and Applied Algebra. 229(10), 108068. mla: Brown, Adam, and Ondrej Draganov. “Discrete Microlocal Morse Theory.” Journal of Pure and Applied Algebra, vol. 229, no. 10, 108068, Elsevier, 2025, doi:10.1016/j.jpaa.2025.108068. short: A. Brown, O. Draganov, Journal of Pure and Applied Algebra 229 (2025). corr_author: '1' date_created: 2025-09-10T05:40:09Z date_published: 2025-10-01T00:00:00Z date_updated: 2026-10-02T11:57:00Z day: '01' ddc: - '510' department: - _id: HeEd doi: 10.1016/j.jpaa.2025.108068 ec_funded: 1 external_id: arxiv: - '2209.14993' file: - access_level: open_access checksum: 39bcad462278c9322ef810af7db67f56 content_type: application/pdf creator: dernst date_created: 2025-12-30T07:55:08Z date_updated: 2025-12-30T07:55:08Z file_id: '20886' file_name: 2025_JourPureAppliedAlgebra_Brown.pdf file_size: 3090836 relation: main_file success: 1 file_date_updated: 2025-12-30T07:55:08Z fulldoi: https://doi.org/10.1016/j.jpaa.2025.108068 has_accepted_license: '1' intvolume: ' 229' issue: '10' language: - iso: eng month: '10' oa: 1 oa_version: Published Version project: - _id: 266A2E9E-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '788183' name: Alpha Shape Theory Extended - _id: 268116B8-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z00342 name: Mathematics, Computer Science - _id: 2561EBF4-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: I02979-N35 name: Persistence and stability of geometric complexes publication: Journal of Pure and Applied Algebra publication_identifier: issn: - 0022-4049 publication_status: published publisher: Elsevier quality_controlled: '1' related_material: record: - id: '18981' relation: earlier_version status: public scopus_import: '1' status: public title: Discrete microlocal Morse theory 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: 229 year: '2025' ... --- DOAJ_listed: '1' OA_place: publisher OA_type: gold PlanS_conform: '1' _id: '20591' abstract: - lang: eng text: In this paper we derive estimates for the Hessian of the logarithm (log-Hessian) for solutions to the heat equation. For initial data in the form of log-Lipschitz perturbation of strongly log-concave measures, the log-Hessian admits an explicit, uniform (in space) lower bound. This yields a new estimate for the Lipschitz constant of a transport map pushing forward the standard Gaussian to a measure in this class. On the other hand, we show that assuming only fast decay of the tails of the initial datum does not suffice to guarantee uniform log-Hessian upper bounds. acknowledgement: This research was funded in part by the Austrian Science Fund (FWF) project 10.55776/F65 and by the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 101034413. The authors thank Professors Jean Dolbeault, Jan Maas, and Nikita Simonov for many useful comments, and Professors Kazuhiro Ishige, Asuka Takatsu, and Yair Shenfeld for inspiring interactions. article_number: '71' article_processing_charge: Yes article_type: original arxiv: 1 author: - first_name: Giovanni full_name: Brigati, Giovanni id: 63ff57e8-1fbb-11ee-88f2-f558ffc59cf1 last_name: Brigati - first_name: Francesco full_name: Pedrotti, Francesco id: d3ac8ac6-dc8d-11ea-abe3-e2a9628c4c3c last_name: Pedrotti citation: ama: Brigati G, Pedrotti F. Heat flow, log-concavity, and Lipschitz transport maps. Electronic Communications in Probability. 2025;30. doi:10.1214/25-ECP717 apa: Brigati, G., & Pedrotti, F. (2025). Heat flow, log-concavity, and Lipschitz transport maps. Electronic Communications in Probability. Institute of Mathematical Statistics. https://doi.org/10.1214/25-ECP717 chicago: Brigati, Giovanni, and Francesco Pedrotti. “Heat Flow, Log-Concavity, and Lipschitz Transport Maps.” Electronic Communications in Probability. Institute of Mathematical Statistics, 2025. https://doi.org/10.1214/25-ECP717. ieee: G. Brigati and F. Pedrotti, “Heat flow, log-concavity, and Lipschitz transport maps,” Electronic Communications in Probability, vol. 30. Institute of Mathematical Statistics, 2025. ista: Brigati G, Pedrotti F. 2025. Heat flow, log-concavity, and Lipschitz transport maps. Electronic Communications in Probability. 30, 71. mla: Brigati, Giovanni, and Francesco Pedrotti. “Heat Flow, Log-Concavity, and Lipschitz Transport Maps.” Electronic Communications in Probability, vol. 30, 71, Institute of Mathematical Statistics, 2025, doi:10.1214/25-ECP717. short: G. Brigati, F. Pedrotti, Electronic Communications in Probability 30 (2025). corr_author: '1' date_created: 2025-11-02T23:01:35Z date_published: 2025-09-25T00:00:00Z date_updated: 2026-10-02T12:20:37Z day: '25' ddc: - '500' department: - _id: JaMa doi: 10.1214/25-ECP717 ec_funded: 1 external_id: arxiv: - '2404.15205' isi: - '001611557000018' file: - access_level: open_access checksum: 67858edbd74658fe38955fa1216f2f18 content_type: application/pdf creator: dernst date_created: 2025-11-04T07:34:05Z date_updated: 2025-11-04T07:34:05Z file_id: '20596' file_name: 2025_ElectronJourProbab_Brigati.pdf file_size: 278078 relation: main_file success: 1 file_date_updated: 2025-11-04T07:34:05Z fulldoi: https://doi.org/10.1214/25-ECP717 has_accepted_license: '1' intvolume: ' 30' isi: 1 language: - iso: eng month: '09' oa: 1 oa_version: Published Version project: - _id: fc31cba2-9c52-11eb-aca3-ff467d239cd2 grant_number: F6504 name: Taming Complexity in Partial Differential Systems - _id: fc2ed2f7-9c52-11eb-aca3-c01059dda49c call_identifier: H2020 grant_number: '101034413' name: 'IST-BRIDGE: International postdoctoral program' publication: Electronic Communications in Probability publication_identifier: eissn: - 1083-589X publication_status: published publisher: Institute of Mathematical Statistics quality_controlled: '1' related_material: record: - id: '17353' relation: earlier_version status: public scopus_import: '1' status: public title: Heat flow, log-concavity, and Lipschitz transport maps 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: 30 year: '2025' ... --- OA_place: repository OA_type: green _id: '20050' abstract: - lang: eng text: We prove upper bounds on the L∞-Wasserstein distance from optimal transport between strongly log-concave probability densities and log-Lipschitz perturbations. In the simplest setting, such a bound amounts to a transport-information inequality involving the L∞-Wasserstein metric and the relative L∞-Fisher information. We show that this inequality can be sharpened significantly in situations where the involved densities are anisotropic. Our proof is based on probabilistic techniques using Langevin dynamics. As an application of these results, we obtain sharp exponential rates of convergence in Fisher’s infinitesimal model from quantitative genetics, generalising recent results by Calvez, Poyato, and Santambrogio in dimension 1 to arbitrary dimensions. acknowledgement: This research was funded in part by the Austrian Science Fund (FWF) project 10.55776/F65 and the Austrian Academy of Science, DOC fellowship nr. 26293. article_processing_charge: No article_type: original arxiv: 1 author: - first_name: Kseniia full_name: Khudiakova, Kseniia id: 4E6DC800-AE37-11E9-AC72-31CAE5697425 last_name: Khudiakova orcid: 0000-0002-6246-1465 - first_name: Jan full_name: Maas, Jan id: 4C5696CE-F248-11E8-B48F-1D18A9856A87 last_name: Maas orcid: 0000-0002-0845-1338 - first_name: Francesco full_name: Pedrotti, Francesco id: d3ac8ac6-dc8d-11ea-abe3-e2a9628c4c3c last_name: Pedrotti citation: ama: Khudiakova K, Maas J, Pedrotti F. L∞-optimal transport of anisotropic log-concave measures and exponential convergence in Fisher’s infinitesimal model. The Annals of Applied Probability. 2025;35(3):1913-1940. doi:10.1214/25-aap2162 apa: Khudiakova, K., Maas, J., & Pedrotti, F. (2025). L∞-optimal transport of anisotropic log-concave measures and exponential convergence in Fisher’s infinitesimal model. The Annals of Applied Probability. Institute of Mathematical Statistics. https://doi.org/10.1214/25-aap2162 chicago: Khudiakova, Kseniia, Jan Maas, and Francesco Pedrotti. “L∞-Optimal Transport of Anisotropic Log-Concave Measures and Exponential Convergence in Fisher’s Infinitesimal Model.” The Annals of Applied Probability. Institute of Mathematical Statistics, 2025. https://doi.org/10.1214/25-aap2162. ieee: K. Khudiakova, J. Maas, and F. Pedrotti, “L∞-optimal transport of anisotropic log-concave measures and exponential convergence in Fisher’s infinitesimal model,” The Annals of Applied Probability, vol. 35, no. 3. Institute of Mathematical Statistics, pp. 1913–1940, 2025. ista: Khudiakova K, Maas J, Pedrotti F. 2025. L∞-optimal transport of anisotropic log-concave measures and exponential convergence in Fisher’s infinitesimal model. The Annals of Applied Probability. 35(3), 1913–1940. mla: Khudiakova, Kseniia, et al. “L∞-Optimal Transport of Anisotropic Log-Concave Measures and Exponential Convergence in Fisher’s Infinitesimal Model.” The Annals of Applied Probability, vol. 35, no. 3, Institute of Mathematical Statistics, 2025, pp. 1913–40, doi:10.1214/25-aap2162. short: K. Khudiakova, J. Maas, F. Pedrotti, The Annals of Applied Probability 35 (2025) 1913–1940. corr_author: '1' date_created: 2025-07-21T08:13:54Z date_published: 2025-06-01T00:00:00Z date_updated: 2026-10-02T12:20:10Z day: '01' department: - _id: JaMa doi: 10.1214/25-aap2162 external_id: arxiv: - '2402.04151' isi: - '001523520000012' fulldoi: https://doi.org/10.1214/25-aap2162 intvolume: ' 35' isi: 1 issue: '3' language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.48550/arXiv.2402.04151 month: '06' oa: 1 oa_version: Preprint page: 1913-1940 project: - _id: fc31cba2-9c52-11eb-aca3-ff467d239cd2 grant_number: F6504 name: Taming Complexity in Partial Differential Systems - _id: 34d33d68-11ca-11ed-8bc3-ec13763c0ca8 grant_number: '26293' name: The impact of deleterious mutations on small populations publication: The Annals of Applied Probability publication_identifier: issn: - 1050-5164 publication_status: published publisher: Institute of Mathematical Statistics quality_controlled: '1' related_material: record: - id: '17352' relation: earlier_version status: public scopus_import: '1' status: public title: L∞-optimal transport of anisotropic log-concave measures and exponential convergence in Fisher’s infinitesimal model type: journal_article user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345 volume: 35 year: '2025' ... --- OA_place: repository OA_type: green _id: '22807' abstract: - lang: eng text: 'Cleavage - the series of rapid cell divisions that follow fertilization - marks the onset of metazoan development and represents a deeply conserved evolutionary process. Across animals, two principal modes exist: complete (holoblastic) and incomplete (meroblastic) cleavage. While holoblastic cleavage resembles conventional cytokinesis both in vitro and in vivo, the mechanisms underlying meroblastic cleavage have remained poorly understood. Using zebrafish embryos as a model, we show that meroblastic cleavage proceeds through a distinct two-step mechanism. The process begins with the assembly and contraction of a large, arc-shaped actomyosin cable. However, this contractile event alone is insufficient to complete division. A second phase, driven by cadherin-mediated membrane adhesion, is required to invaginate the furrow ridge. Strikingly, this transition depends on mechanical uncoupling of the contractile cable from the surrounding cortex. We demonstrate that such uncoupling arises from an active nematic instability, which both enhances contractility along the cable and generates actin depletion zones that relieve lateral connections. Together, these findings reveal that meroblastic cleavage is governed not by a single actomyosin-based event but by a sequential interplay between cytoskeletal contraction and cadherin-dependent adhesion, highlighting a mechanism fundamentally distinct from canonical cytokinesis.' acknowledgement: We are grateful to the members of the Hannezo and Heisenberg groups for discussions and technical advice. We also thank the Imaging and Optics Facility and the Lab Support Facility at ISTA for their continuous support. Y.I.L. acknowledges funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skodowska-Curie Grant Agreement No. 101034413. The research was supported by funding to C.-P.H. from the NOMIS Foundation (Project ID 1.844) and to E.H. from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement no. 851288). article_processing_charge: No author: - first_name: Xin full_name: Tong, Xin id: 50F65CDC-AA30-11E9-A72B-8A12E6697425 last_name: Tong - first_name: Yuting I full_name: Li, Yuting I id: ee7a5ca8-8b71-11ed-b662-b3341c05b7eb last_name: Li - first_name: Joséphine full_name: Schelle, Joséphine last_name: Schelle - first_name: Edouard B full_name: Hannezo, Edouard B id: 3A9DB764-F248-11E8-B48F-1D18A9856A87 last_name: Hannezo orcid: 0000-0001-6005-1561 - first_name: Carl-Philipp J full_name: Heisenberg, Carl-Philipp J id: 39427864-F248-11E8-B48F-1D18A9856A87 last_name: Heisenberg orcid: 0000-0002-0912-4566 biorxivid: 1 citation: ama: Tong X, Li YI, Schelle J, Hannezo EB, Heisenberg C-PJ. Non-canonical cytokinesis driven by mechanical uncoupling via nematic flows and adhesion-based invagination. bioRxiv. doi:10.1101/2025.10.15.682552 apa: Tong, X., Li, Y. I., Schelle, J., Hannezo, E. B., & Heisenberg, C.-P. J. (n.d.). Non-canonical cytokinesis driven by mechanical uncoupling via nematic flows and adhesion-based invagination. bioRxiv. https://doi.org/10.1101/2025.10.15.682552 chicago: Tong, Xin, Yuting I Li, Joséphine Schelle, Edouard B Hannezo, and Carl-Philipp J Heisenberg. “Non-Canonical Cytokinesis Driven by Mechanical Uncoupling via Nematic Flows and Adhesion-Based Invagination.” BioRxiv, n.d. https://doi.org/10.1101/2025.10.15.682552. ieee: X. Tong, Y. I. Li, J. Schelle, E. B. Hannezo, and C.-P. J. Heisenberg, “Non-canonical cytokinesis driven by mechanical uncoupling via nematic flows and adhesion-based invagination,” bioRxiv. . ista: Tong X, Li YI, Schelle J, Hannezo EB, Heisenberg C-PJ. Non-canonical cytokinesis driven by mechanical uncoupling via nematic flows and adhesion-based invagination. bioRxiv, 10.1101/2025.10.15.682552. mla: Tong, Xin, et al. “Non-Canonical Cytokinesis Driven by Mechanical Uncoupling via Nematic Flows and Adhesion-Based Invagination.” BioRxiv, doi:10.1101/2025.10.15.682552. short: X. Tong, Y.I. Li, J. Schelle, E.B. Hannezo, C.-P.J. Heisenberg, BioRxiv (n.d.). corr_author: '1' date_created: 2026-09-04T12:32:21Z date_published: 2025-10-15T00:00:00Z date_updated: 2026-10-05T08:56:09Z day: '15' department: - _id: EdHa - _id: CaHe doi: 10.1101/2025.10.15.682552 ec_funded: 1 external_id: biorxivid: - 2025.10.15.682552 fulldoi: https://doi.org/10.1101/2025.10.15.682552 language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.1101/2025.10.15.682552 month: '10' oa: 1 oa_version: Preprint project: - _id: fc2ed2f7-9c52-11eb-aca3-c01059dda49c call_identifier: H2020 grant_number: '101034413' name: 'IST-BRIDGE: International postdoctoral program' - _id: 05943252-7A3F-11EA-A408-12923DDC885E call_identifier: H2020 grant_number: '851288' name: Design Principles of Branching Morphogenesis - _id: 9B861AAC-BA93-11EA-9121-9846C619BF3A name: NOMIS Fellowship Program publication: bioRxiv publication_status: draft related_material: record: - id: '22804' relation: dissertation_contains status: public status: public title: Non-canonical cytokinesis driven by mechanical uncoupling via nematic flows and adhesion-based invagination tmp: image: /images/cc_by_nc.png legal_code_url: https://creativecommons.org/licenses/by-nc/4.0/legalcode name: Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) short: CC BY-NC (4.0) type: preprint user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9 year: '2025' ... --- OA_place: publisher OA_type: hybrid PlanS_conform: '1' _id: '20705' abstract: - lang: eng text: Optical tweezers are widely used as a highly sensitive tool to measure forces on micron-scale particles. One such application is the measurement of the electric charge of a particle, which can be done with high precision in liquids, air, or vacuum. We experimentally investigate how the trapping laser itself can electrically charge such a particle, in our case a ∼1  μ⁢m SiO2 sphere in air. We model the charging mechanism as a two-photon process which reproduces the experimental data with high fidelity. acknowledged_ssus: - _id: M-Shop - _id: ScienComp acknowledgement: We thank Todor Asenov and Abdulhamid Baghdadi for their outstanding technical support and Dr. Michael Gleichweit and Mercede Azizbaig Mohajer for the helpful discussions. This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (Grant Agreements No. 949120 and No. 805041) and the Swiss National Science Foundation (SNSF, Project No. 200021-236446). This research was supported by the Scientific Service Units of the Institute of Science and Technology Austria (ISTA) through resources provided by the Miba Machine Shop and the Scientific Computing service unit. article_number: '218202' article_processing_charge: Yes (via OA deal) article_type: original arxiv: 1 author: - first_name: Andrea full_name: Stöllner, Andrea id: 4bdcf7f6-eb97-11eb-a6c2-9981bbdc3bed last_name: Stöllner orcid: 0000-0002-0464-8440 - first_name: Isaac C full_name: Lenton, Isaac C id: a550210f-223c-11ec-8182-e2d45e817efb last_name: Lenton orcid: 0000-0002-5010-6984 - first_name: Artem full_name: Volosniev, Artem id: 37D278BC-F248-11E8-B48F-1D18A9856A87 last_name: Volosniev orcid: 0000-0003-0393-5525 - first_name: James full_name: Millen, James last_name: Millen - first_name: Renjiro full_name: Shibuya, Renjiro last_name: Shibuya - first_name: Hisao full_name: Ishii, Hisao last_name: Ishii - first_name: Dmytro full_name: Rak, Dmytro id: 70313b46-47c2-11ec-9e88-cd79101918fe last_name: Rak - first_name: Zhanybek full_name: Alpichshev, Zhanybek id: 45E67A2A-F248-11E8-B48F-1D18A9856A87 last_name: Alpichshev orcid: 0000-0002-7183-5203 - first_name: Grégory full_name: David, Grégory last_name: David - first_name: Ruth full_name: Signorell, Ruth last_name: Signorell - first_name: Caroline J full_name: Muller, Caroline J id: f978ccb0-3f7f-11eb-b193-b0e2bd13182b last_name: Muller orcid: 0000-0001-5836-5350 - first_name: Scott R full_name: Waitukaitis, Scott R id: 3A1FFC16-F248-11E8-B48F-1D18A9856A87 last_name: Waitukaitis orcid: 0000-0002-2299-3176 citation: ama: Stöllner A, Lenton IC, Volosniev A, et al. Using optical tweezers to simultaneously trap, charge, and measure the charge of a microparticle in air. Physical Review Letters. 2025;135(21). doi:10.1103/5xd9-4tjj apa: Stöllner, A., Lenton, I. C., Volosniev, A., Millen, J., Shibuya, R., Ishii, H., … Waitukaitis, S. R. (2025). Using optical tweezers to simultaneously trap, charge, and measure the charge of a microparticle in air. Physical Review Letters. American Physical Society. https://doi.org/10.1103/5xd9-4tjj chicago: Stöllner, Andrea, Isaac C Lenton, Artem Volosniev, James Millen, Renjiro Shibuya, Hisao Ishii, Dmytro Rak, et al. “Using Optical Tweezers to Simultaneously Trap, Charge, and Measure the Charge of a Microparticle in Air.” Physical Review Letters. American Physical Society, 2025. https://doi.org/10.1103/5xd9-4tjj. ieee: A. Stöllner et al., “Using optical tweezers to simultaneously trap, charge, and measure the charge of a microparticle in air,” Physical Review Letters, vol. 135, no. 21. American Physical Society, 2025. ista: Stöllner A, Lenton IC, Volosniev A, Millen J, Shibuya R, Ishii H, Rak D, Alpichshev Z, David G, Signorell R, Muller CJ, Waitukaitis SR. 2025. Using optical tweezers to simultaneously trap, charge, and measure the charge of a microparticle in air. Physical Review Letters. 135(21), 218202. mla: Stöllner, Andrea, et al. “Using Optical Tweezers to Simultaneously Trap, Charge, and Measure the Charge of a Microparticle in Air.” Physical Review Letters, vol. 135, no. 21, 218202, American Physical Society, 2025, doi:10.1103/5xd9-4tjj. short: A. Stöllner, I.C. Lenton, A. Volosniev, J. Millen, R. Shibuya, H. Ishii, D. Rak, Z. Alpichshev, G. David, R. Signorell, C.J. Muller, S.R. Waitukaitis, Physical Review Letters 135 (2025). corr_author: '1' date_created: 2025-11-30T23:02:07Z date_published: 2025-11-21T00:00:00Z date_updated: 2026-10-09T11:09:09Z day: '21' ddc: - '530' - '550' department: - _id: ZhAl - _id: CaMu - _id: ScWa doi: 10.1103/5xd9-4tjj ec_funded: 1 external_id: arxiv: - '2507.17591' file: - access_level: open_access checksum: a5f76b1230cc7b039ecd0dbd6f99e775 content_type: application/pdf creator: dernst date_created: 2025-12-01T08:19:46Z date_updated: 2025-12-01T08:19:46Z file_id: '20717' file_name: 2025_PhysReviewLetters_Stoellner.pdf file_size: 1761373 relation: main_file success: 1 file_date_updated: 2025-12-01T08:19:46Z fulldoi: https://doi.org/10.1103/5xd9-4tjj has_accepted_license: '1' intvolume: ' 135' issue: '21' language: - iso: eng month: '11' oa: 1 oa_version: Published Version project: - _id: 0aa60e99-070f-11eb-9043-a6de6bdc3afa call_identifier: H2020 grant_number: '949120' name: 'Tribocharge: a multi-scale approach to an enduring problem in physics' - _id: 629205d8-2b32-11ec-9570-e1356ff73576 call_identifier: H2020 grant_number: '805041' name: Organization of CLoUdS, and implications of Tropical cyclones and for the Energetics of the tropics, in current and waRming climate publication: Physical Review Letters publication_identifier: eissn: - 1079-7114 issn: - 0031-9007 publication_status: published publisher: American Physical Society quality_controlled: '1' related_material: link: - description: News on ISTA website relation: press_release url: https://ista.ac.at/en/news/trapping-particles-to-explain-lightning/ record: - id: '23033' relation: dissertation_contains status: public scopus_import: '1' status: public title: Using optical tweezers to simultaneously trap, charge, and measure the charge of a microparticle in air 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: ba8df636-2132-11f1-aed0-ed93e2281fdd volume: 135 year: '2025' ... --- DOAJ_listed: '1' OA_place: publisher OA_type: gold PlanS_conform: '1' _id: '20662' abstract: - lang: eng text: Task-based functional magnetic resonance imaging (fMRI) reveals individual differences in neural correlates of cognition but faces scalability challenges due to cognitive demands, protocol variability, and limited task coverage in large datasets. Here, we propose DeepTaskGen, a deep-learning approach that synthesizes non-acquired task-based contrast maps from resting-state (rs-) fMRI. We validate this approach using the Human Connectome Project lifespan data, then generate 47 contrast maps from 7 different cognitive tasks for over 20,000 individuals from UK Biobank. DeepTaskGen outperforms several benchmarks in generating synthetic task-contrast maps, achieving superior reconstruction performance while retaining inter-individual variation essential for biomarker development. We further show comparable or superior predictive performance of synthetic maps relative to actual maps and rs-connectomes across diverse demographic, cognitive, and clinical variables. This approach facilitates the study of individual differences and the generation of task-related biomarkers by enabling the generation of arbitrary functional cognitive tasks from readily available rs-fMRI data. acknowledgement: 'Funded by the European Union (Grant agreement No 101057429). Complementary funding was received by UK Research and Innovation (UKRI) under the UK government’s Horizon Europe funding guarantee (10131373 and 10038599) and the National Key R&D Program of Ministry of Science and Technology of China (MOST 2023YFE0199700). Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union, the European Health and Digital Executive Agency (HADEA), UKRI or MOST. Neither the European Union nor HADEA nor UKRI nor MOST can be held responsible for them. This work has also been supported by a Grant from the German Research Foundation to the ENIGMA task-based fMRI Working Group (DFG ER 724/4–1, WA 1539/11–1). Data used in this study were provided in part by the Human Connectome Project, WU-Minn Consortium (principal investigators: D. Van Essen and K. Ugurbil; grant number 1U54MH091657), funded by the 16 National Institutes of Health (NIH) institutes and centers supporting the NIH Blueprint for Neuroscience Research, and by the McDonnell Center for Systems Neuroscience at Washington University. Additionally, this research utilized data obtained from UK Biobank, a large-scale biomedical database. Open Access funding enabled and organized by Projekt DEAL.' article_number: '1572' article_processing_charge: Yes article_type: original author: - first_name: Emin full_name: Serin, Emin last_name: Serin - first_name: Kerstin full_name: Ritter, Kerstin last_name: Ritter - first_name: Gunter full_name: Schumann, Gunter last_name: Schumann - first_name: Tobias full_name: Banaschewski, Tobias last_name: Banaschewski - first_name: Andre full_name: Marquand, Andre last_name: Marquand - first_name: Henrik full_name: Walter, Henrik last_name: Walter - first_name: George full_name: Ogoh, George last_name: Ogoh - first_name: Bernd Carsten full_name: Stahl, Bernd Carsten last_name: Stahl - first_name: Ragnhild full_name: Brandlistuen, Ragnhild last_name: Brandlistuen - first_name: Tamara full_name: Schikowski, Tamara last_name: Schikowski - first_name: Allan H. full_name: Young, Allan H. last_name: Young - first_name: Yu full_name: Xinyang, Yu last_name: Xinyang - first_name: Zuo full_name: Zhang, Zuo last_name: Zhang - first_name: Kofoworola full_name: Agunbiade, Kofoworola last_name: Agunbiade - first_name: Di full_name: Chen, Di last_name: Chen - first_name: Sylvane full_name: Desrivières, Sylvane last_name: Desrivières - first_name: Nicholas full_name: Clinton, Nicholas last_name: Clinton - first_name: Paul full_name: Thompson, Paul last_name: Thompson - first_name: Venessa full_name: Köhler, Venessa last_name: Köhler - first_name: Ameli full_name: Schwalber, Ameli last_name: Schwalber - first_name: Vince D. full_name: Calhoun, Vince D. last_name: Calhoun - first_name: Xiao full_name: Chang, Xiao last_name: Chang - first_name: Yanqing full_name: Zhang, Yanqing last_name: Zhang - first_name: Yuzhu full_name: Li, Yuzhu last_name: Li - first_name: Yuxiang full_name: Dai, Yuxiang last_name: Dai - first_name: Jiacan full_name: Yuan, Jiacan last_name: Yuan - first_name: Yunman full_name: Xia, Yunman last_name: Xia - first_name: Tianye full_name: Jia, Tianye last_name: Jia - first_name: Paul full_name: Renner, Paul last_name: Renner - first_name: Sören full_name: Hese, Sören last_name: Hese - first_name: Bernhard full_name: Spanlang, Bernhard last_name: Spanlang - first_name: Charlie full_name: Pearmund, Charlie last_name: Pearmund - first_name: Anastasios Polykarpos full_name: Athanasiadis, Anastasios Polykarpos last_name: Athanasiadis - first_name: Spase full_name: Petkoski, Spase last_name: Petkoski - first_name: Viktor full_name: Jirsa, Viktor last_name: Jirsa - first_name: Karen full_name: Schmitt, Karen last_name: Schmitt - first_name: Johannes H. full_name: Wilbertz, Johannes H. last_name: Wilbertz - first_name: Myrto full_name: Patraskaki, Myrto last_name: Patraskaki - first_name: Peter full_name: Sommer, Peter last_name: Sommer - first_name: Stefanie full_name: Heilmann-Heimbach, Stefanie last_name: Heilmann-Heimbach - first_name: Carina M. full_name: Mathey, Carina M. last_name: Mathey - first_name: Abigail J. full_name: Miller, Abigail J. last_name: Miller - first_name: Isabelle full_name: Claus, Isabelle last_name: Claus - first_name: Markus M. full_name: Nöthen, Markus M. last_name: Nöthen - first_name: Per full_name: Hoffmann, Per last_name: Hoffmann - first_name: Andreas J. full_name: Forstner, Andreas J. last_name: Forstner - first_name: Alvaro full_name: Pastor, Alvaro last_name: Pastor - first_name: Jaime full_name: Gallego, Jaime last_name: Gallego - first_name: Reiya full_name: Itatani, Reiya last_name: Itatani - first_name: Francisco full_name: Eiroa-Orosa, Francisco last_name: Eiroa-Orosa - first_name: Guillem full_name: Feixas, Guillem last_name: Feixas - first_name: Mel full_name: Slater, Mel last_name: Slater - first_name: Gaia full_name: Novarino, Gaia id: 3E57A680-F248-11E8-B48F-1D18A9856A87 last_name: Novarino orcid: 0000-0002-7673-7178 - first_name: Sarah Jane full_name: Böttger, Sarah Jane last_name: Böttger - first_name: Mira full_name: Tschorn, Mira last_name: Tschorn - first_name: Michael full_name: Rapp, Michael last_name: Rapp - first_name: Helga full_name: Ask, Helga last_name: Ask - first_name: Rikka full_name: Kjelkenes, Rikka last_name: Kjelkenes - first_name: Sara full_name: Fernandez, Sara last_name: Fernandez - first_name: Dennis full_name: Van Der Meer, Dennis last_name: Van Der Meer - first_name: Lars T. full_name: Westlye, Lars T. last_name: Westlye - first_name: Ole A. full_name: Andreassen, Ole A. last_name: Andreassen - first_name: Rieke full_name: Aden, Rieke last_name: Aden - first_name: Beke full_name: Seefried, Beke last_name: Seefried - first_name: Frauke full_name: Nees, Frauke last_name: Nees - first_name: Maja full_name: Neidhart, Maja last_name: Neidhart - first_name: Argyris full_name: Stringaris, Argyris last_name: Stringaris - first_name: Emanuel full_name: Schwarz, Emanuel last_name: Schwarz - first_name: Nathalie full_name: Holz, Nathalie last_name: Holz - first_name: Heike full_name: Tost, Heike last_name: Tost - first_name: Andreas full_name: Meyer-Lindenberg, Andreas last_name: Meyer-Lindenberg - first_name: Nina full_name: Christmann, Nina last_name: Christmann - first_name: Karina full_name: Janson, Karina last_name: Janson - first_name: Kerstin full_name: Schepanski, Kerstin last_name: Schepanski - first_name: Tatjana full_name: Schütz, Tatjana last_name: Schütz - first_name: Ulrike Helene full_name: Taron, Ulrike Helene last_name: Taron - first_name: Roland full_name: Eils, Roland last_name: Eils - first_name: Jean Charles full_name: Roy, Jean Charles last_name: Roy - first_name: Tristram A. full_name: Lett, Tristram A. last_name: Lett - first_name: Hedi full_name: Kebir, Hedi last_name: Kebir - first_name: Elli full_name: Polemiti, Elli last_name: Polemiti - first_name: Esther full_name: Hitchen, Esther last_name: Hitchen - first_name: Marcel full_name: Jentsch, Marcel last_name: Jentsch - first_name: Emin full_name: Serin, Emin last_name: Serin - first_name: Antoine full_name: Bernas, Antoine last_name: Bernas - first_name: Nilakshi full_name: Vaidya, Nilakshi last_name: Vaidya - first_name: Sven full_name: Twardziok, Sven last_name: Twardziok - first_name: Markus full_name: Ralser, Markus last_name: Ralser - first_name: Andreas full_name: Heinz, Andreas last_name: Heinz - first_name: Gunter full_name: Schumann, Gunter last_name: Schumann citation: ama: Serin E, Ritter K, Schumann G, et al. Generating synthetic task-based brain fingerprints for population neuroscience using deep learning. Communications Biology. 2025;8. doi:10.1038/s42003-025-09158-6 apa: Serin, E., Ritter, K., Schumann, G., Banaschewski, T., Marquand, A., Walter, H., … Schumann, G. (2025). Generating synthetic task-based brain fingerprints for population neuroscience using deep learning. Communications Biology. Springer Nature. https://doi.org/10.1038/s42003-025-09158-6 chicago: Serin, Emin, Kerstin Ritter, Gunter Schumann, Tobias Banaschewski, Andre Marquand, Henrik Walter, George Ogoh, et al. “Generating Synthetic Task-Based Brain Fingerprints for Population Neuroscience Using Deep Learning.” Communications Biology. Springer Nature, 2025. https://doi.org/10.1038/s42003-025-09158-6. ieee: E. Serin et al., “Generating synthetic task-based brain fingerprints for population neuroscience using deep learning,” Communications Biology, vol. 8. Springer Nature, 2025. ista: Serin E, Ritter K, Schumann G, Banaschewski T, Marquand A, Walter H, Ogoh G, Stahl BC, Brandlistuen R, Schikowski T, Young AH, Xinyang Y, Zhang Z, Agunbiade K, Chen D, Desrivières S, Clinton N, Thompson P, Köhler V, Schwalber A, Calhoun VD, Chang X, Zhang Y, Li Y, Dai Y, Yuan J, Xia Y, Jia T, Renner P, Hese S, Spanlang B, Pearmund C, Athanasiadis AP, Petkoski S, Jirsa V, Schmitt K, Wilbertz JH, Patraskaki M, Sommer P, Heilmann-Heimbach S, Mathey CM, Miller AJ, Claus I, Nöthen MM, Hoffmann P, Forstner AJ, Pastor A, Gallego J, Itatani R, Eiroa-Orosa F, Feixas G, Slater M, Novarino G, Böttger SJ, Tschorn M, Rapp M, Ask H, Kjelkenes R, Fernandez S, Van Der Meer D, Westlye LT, Andreassen OA, Aden R, Seefried B, Nees F, Neidhart M, Stringaris A, Schwarz E, Holz N, Tost H, Meyer-Lindenberg A, Christmann N, Janson K, Schepanski K, Schütz T, Taron UH, Eils R, Roy JC, Lett TA, Kebir H, Polemiti E, Hitchen E, Jentsch M, Serin E, Bernas A, Vaidya N, Twardziok S, Ralser M, Heinz A, Schumann G. 2025. Generating synthetic task-based brain fingerprints for population neuroscience using deep learning. Communications Biology. 8, 1572. mla: Serin, Emin, et al. “Generating Synthetic Task-Based Brain Fingerprints for Population Neuroscience Using Deep Learning.” Communications Biology, vol. 8, 1572, Springer Nature, 2025, doi:10.1038/s42003-025-09158-6. short: E. Serin, K. Ritter, G. Schumann, T. Banaschewski, A. Marquand, H. Walter, G. Ogoh, B.C. Stahl, R. Brandlistuen, T. Schikowski, A.H. Young, Y. Xinyang, Z. Zhang, K. Agunbiade, D. Chen, S. Desrivières, N. Clinton, P. Thompson, V. Köhler, A. Schwalber, V.D. Calhoun, X. Chang, Y. Zhang, Y. Li, Y. Dai, J. Yuan, Y. Xia, T. Jia, P. Renner, S. Hese, B. Spanlang, C. Pearmund, A.P. Athanasiadis, S. Petkoski, V. Jirsa, K. Schmitt, J.H. Wilbertz, M. Patraskaki, P. Sommer, S. Heilmann-Heimbach, C.M. Mathey, A.J. Miller, I. Claus, M.M. Nöthen, P. Hoffmann, A.J. Forstner, A. Pastor, J. Gallego, R. Itatani, F. Eiroa-Orosa, G. Feixas, M. Slater, G. Novarino, S.J. Böttger, M. Tschorn, M. Rapp, H. Ask, R. Kjelkenes, S. Fernandez, D. Van Der Meer, L.T. Westlye, O.A. Andreassen, R. Aden, B. Seefried, F. Nees, M. Neidhart, A. Stringaris, E. Schwarz, N. Holz, H. Tost, A. Meyer-Lindenberg, N. Christmann, K. Janson, K. Schepanski, T. Schütz, U.H. Taron, R. Eils, J.C. Roy, T.A. Lett, H. Kebir, E. Polemiti, E. Hitchen, M. Jentsch, E. Serin, A. Bernas, N. Vaidya, S. Twardziok, M. Ralser, A. Heinz, G. Schumann, Communications Biology 8 (2025). date_created: 2025-11-23T23:01:38Z date_published: 2025-12-01T00:00:00Z date_updated: 2026-10-12T11:59:45Z day: '01' ddc: - '570' department: - _id: GaNo doi: 10.1038/s42003-025-09158-6 external_id: isi: - '001614464000001' pmid: - '41238730' file: - access_level: open_access checksum: b8b3c1abe7048a09b920082a37e786a5 content_type: application/pdf creator: dernst date_created: 2025-11-24T09:12:19Z date_updated: 2025-11-24T09:12:19Z file_id: '20675' file_name: 2025_CommunicationsBiology_Serin.pdf file_size: 1588155 relation: main_file success: 1 file_date_updated: 2025-11-24T09:12:19Z fulldoi: https://doi.org/10.1038/s42003-025-09158-6 has_accepted_license: '1' intvolume: ' 8' isi: 1 language: - iso: eng month: '12' oa: 1 oa_version: Published Version pmid: 1 publication: Communications Biology publication_identifier: eissn: - 2399-3642 publication_status: published publisher: Springer Nature quality_controlled: '1' related_material: link: - relation: erratum url: https://doi.org/10.1038/s42003-026-10937-y scopus_import: '1' status: public title: Generating synthetic task-based brain fingerprints for population neuroscience using deep learning tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 8 year: '2025' ... --- OA_place: publisher OA_type: gold _id: '21281' abstract: - lang: eng text: "A strategy profile in a multi-player game is a Nash equilibrium if no player can unilaterally deviate to achieve a strictly better payoff. A profile is an ε-Nash equilibrium if no player can gain more than ε by unilaterally deviating from their strategy. In this work, we use ε-Nash equilibria to approximate the computation of Nash equilibria. Specifically, we focus on turn-based, multiplayer stochastic games played on graphs, where players are restricted to stationary strategies - strategies that use randomness but not memory.\r\nThe problem of deciding the constrained existence of stationary Nash equilibria - where each player’s payoff must lie within a given interval - is known to be ∃ℝ-complete in such a setting (Hansen and Sølvsten, 2020). We extend this line of work to stationary ε-Nash equilibria and present an algorithm that solves the following promise problem: given a game with a Nash equilibrium satisfying the constraints, compute an ε-Nash equilibrium that ε-satisfies those same constraints - satisfies the constraints up to an ε additive error. Our algorithm runs in FNP^NP time.\r\nTo achieve this, we first show that if a constrained Nash equilibrium exists, then one exists where the non-zero probabilities are at least an inverse of a double-exponential in the input. We further prove that such a strategy can be encoded using floating-point representations, as in the work of Frederiksen and Miltersen (2013), which finally gives us our FNP^NP algorithm. \r\nWe further show that the decision version of the promise problem is NP-hard. Finally, we show a partial tightness result by proving a lower bound for such techniques: if a constrained Nash equilibrium exists, then there must be one where the probabilities in the strategies are double-exponentially small." acknowledgement: "This work is a part of project VAMOS that has received funding from the European\r\nResearch Council (ERC), grant agreement No 101020093.\r\n" alternative_title: - LIPIcs article_processing_charge: Yes arxiv: 1 author: - first_name: Ali full_name: Asadi, Ali id: 02d96aae-000e-11ec-b801-cadd0a5eefbb last_name: Asadi - first_name: Leonard full_name: Brice, Leonard last_name: Brice - first_name: Krishnendu full_name: Chatterjee, Krishnendu id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87 last_name: Chatterjee orcid: 0000-0002-4561-241X - first_name: K. S. full_name: Thejaswini, K. S. id: 3807fb92-fdc1-11ee-bb4a-b4d8a431c753 last_name: Thejaswini citation: ama: 'Asadi A, Brice L, Chatterjee K, Thejaswini KS. ε-stationary Nash equilibria in multi-player stochastic graph games. In: 45th Annual Conference on Foundations of Software Technology and Theoretical Computer Science. Vol 360. Schloss Dagstuhl - Leibniz-Zentrum für Informatik; 2025:9:1-9:17. doi:10.4230/lipics.fsttcs.2025.9' apa: 'Asadi, A., Brice, L., Chatterjee, K., & Thejaswini, K. S. (2025). ε-stationary Nash equilibria in multi-player stochastic graph games. In 45th Annual Conference on Foundations of Software Technology and Theoretical Computer Science (Vol. 360, p. 9:1-9:17). Pilani, India: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/lipics.fsttcs.2025.9' chicago: Asadi, Ali, Leonard Brice, Krishnendu Chatterjee, and K. S. Thejaswini. “ε-Stationary Nash Equilibria in Multi-Player Stochastic Graph Games.” In 45th Annual Conference on Foundations of Software Technology and Theoretical Computer Science, 360:9:1-9:17. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2025. https://doi.org/10.4230/lipics.fsttcs.2025.9. ieee: A. Asadi, L. Brice, K. Chatterjee, and K. S. Thejaswini, “ε-stationary Nash equilibria in multi-player stochastic graph games,” in 45th Annual Conference on Foundations of Software Technology and Theoretical Computer Science, Pilani, India, 2025, vol. 360, p. 9:1-9:17. ista: 'Asadi A, Brice L, Chatterjee K, Thejaswini KS. 2025. ε-stationary Nash equilibria in multi-player stochastic graph games. 45th Annual Conference on Foundations of Software Technology and Theoretical Computer Science. FSTTCS: Conference on Foundations of Software Technology and Theoretical Computer Science, LIPIcs, vol. 360, 9:1-9:17.' mla: Asadi, Ali, et al. “ε-Stationary Nash Equilibria in Multi-Player Stochastic Graph Games.” 45th Annual Conference on Foundations of Software Technology and Theoretical Computer Science, vol. 360, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2025, p. 9:1-9:17, doi:10.4230/lipics.fsttcs.2025.9. short: A. Asadi, L. Brice, K. Chatterjee, K.S. Thejaswini, in:, 45th Annual Conference on Foundations of Software Technology and Theoretical Computer Science, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2025, p. 9:1-9:17. conference: end_date: 2025-12-19 location: Pilani, India name: 'FSTTCS: Conference on Foundations of Software Technology and Theoretical Computer Science' start_date: 2025-12-17 corr_author: '1' date_created: 2026-02-17T08:27:14Z date_published: 2025-12-09T00:00:00Z date_updated: 2026-10-12T13:38:13Z day: '09' ddc: - '000' department: - _id: KrCh - _id: GradSch doi: 10.4230/lipics.fsttcs.2025.9 ec_funded: 1 external_id: arxiv: - '2508.15356' file: - access_level: open_access checksum: a66343e3ccc4a9cc5bc699c03d5764ff content_type: application/pdf creator: dernst date_created: 2026-02-18T09:13:25Z date_updated: 2026-02-18T09:13:25Z file_id: '21316' file_name: 2025_FSTTCS_Asadi.pdf file_size: 1054007 relation: main_file success: 1 file_date_updated: 2026-02-18T09:13:25Z fulldoi: https://doi.org/10.4230/lipics.fsttcs.2025.9 has_accepted_license: '1' intvolume: ' 360' language: - iso: eng month: '12' oa: 1 oa_version: Published Version page: 9:1-9:17 project: - _id: 62781420-2b32-11ec-9570-8d9b63373d4d call_identifier: H2020 grant_number: '101020093' name: Vigilant Algorithmic Monitoring of Software publication: 45th Annual Conference on Foundations of Software Technology and Theoretical Computer Science publication_identifier: isbn: - '9783959774062' publication_status: published publisher: Schloss Dagstuhl - Leibniz-Zentrum für Informatik quality_controlled: '1' related_material: record: - id: '23079' relation: dissertation_contains status: public status: public title: ε-stationary Nash equilibria in multi-player stochastic graph games tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 360 year: '2025' ... --- OA_place: publisher OA_type: hybrid _id: '23129' abstract: - lang: eng text: "Abstract\r\n The Arabidopsis root apical meristem is an excellent model for studying plant organ growth. This involves a coordinated process of cell division, elongation, and differentiation, with each tissue type developing according to its own schedule. Among these tissues, the protophloem is particularly important, differentiating early to supply nutrients and signalling molecules to the growing root tip. The OCTOPUS (OPS) protein and its homologue OPS-LIKE 2 (OPL2) are essential for proper root protophloem differentiation and, probably through this role, indirectly promote root growth. Here, we explored the roles of the other three OPS homologues in Arabidopsis, OPL1, OPL3, and OPL4. OPS/OPL genes exhibited overlapping expression patterns and functions, with a high degree of redundancy among them. Although higher order mutants did not display more severe phloem defects, they exhibited significantly reduced root growth compared with the ops opl2 mutant. These results indicate a direct contribution of the investigated OPL genes to meristematic activity. While our focus was on root growth, the OPS/OPL gene family also plays a positive role in regulating shoot growth, emphasizing its broader impact on plant development. Furthermore, our analyses reiterate the central role of OPS and the phloem domain in controlling overall plant growth." article_processing_charge: Yes (in subscription journal) article_type: original author: - first_name: Simona full_name: Crivelli, Simona last_name: Crivelli - first_name: Kai full_name: Bartusch, Kai id: 0c51b9f5-90c8-11f1-b4ef-9ad5d3d9a34a last_name: Bartusch orcid: 0000-0003-2708-5545 - first_name: M Aguila full_name: Ruiz-Sola, M Aguila last_name: Ruiz-Sola - first_name: Mario full_name: Coiro, Mario last_name: Coiro - first_name: Signe full_name: Schmidt Kjølner Hansen, Signe last_name: Schmidt Kjølner Hansen - first_name: Elisabeth full_name: Truernit, Elisabeth last_name: Truernit citation: ama: Crivelli S, Bartusch K, Ruiz-Sola MA, Coiro M, Schmidt Kjølner Hansen S, Truernit E. Distinct and redundant roles of the Arabidopsis OCTOPUS gene family in plant growth beyond phloem development. Journal of Experimental Botany. 2025;76(6):1752-1766. doi:10.1093/jxb/eraf010 apa: Crivelli, S., Bartusch, K., Ruiz-Sola, M. A., Coiro, M., Schmidt Kjølner Hansen, S., & Truernit, E. (2025). Distinct and redundant roles of the Arabidopsis OCTOPUS gene family in plant growth beyond phloem development. Journal of Experimental Botany. Oxford University Press. https://doi.org/10.1093/jxb/eraf010 chicago: Crivelli, Simona, Kai Bartusch, M Aguila Ruiz-Sola, Mario Coiro, Signe Schmidt Kjølner Hansen, and Elisabeth Truernit. “Distinct and Redundant Roles of the Arabidopsis OCTOPUS Gene Family in Plant Growth beyond Phloem Development.” Journal of Experimental Botany. Oxford University Press, 2025. https://doi.org/10.1093/jxb/eraf010. ieee: S. Crivelli, K. Bartusch, M. A. Ruiz-Sola, M. Coiro, S. Schmidt Kjølner Hansen, and E. Truernit, “Distinct and redundant roles of the Arabidopsis OCTOPUS gene family in plant growth beyond phloem development,” Journal of Experimental Botany, vol. 76, no. 6. Oxford University Press, pp. 1752–1766, 2025. ista: Crivelli S, Bartusch K, Ruiz-Sola MA, Coiro M, Schmidt Kjølner Hansen S, Truernit E. 2025. Distinct and redundant roles of the Arabidopsis OCTOPUS gene family in plant growth beyond phloem development. Journal of Experimental Botany. 76(6), 1752–1766. mla: Crivelli, Simona, et al. “Distinct and Redundant Roles of the Arabidopsis OCTOPUS Gene Family in Plant Growth beyond Phloem Development.” Journal of Experimental Botany, vol. 76, no. 6, Oxford University Press, 2025, pp. 1752–66, doi:10.1093/jxb/eraf010. short: S. Crivelli, K. Bartusch, M.A. Ruiz-Sola, M. Coiro, S. Schmidt Kjølner Hansen, E. Truernit, Journal of Experimental Botany 76 (2025) 1752–1766. date_created: 2026-10-13T11:14:54Z date_published: 2025-04-09T00:00:00Z date_updated: 2026-10-14T09:05:24Z day: '09' ddc: - '580' doi: 10.1093/jxb/eraf010 extern: '1' external_id: pmid: - '39798141' fulldoi: https://doi.org/10.1093/jxb/eraf010 has_accepted_license: '1' intvolume: ' 76' issue: '6' language: - iso: eng month: '04' oa_version: Published Version page: 1752-1766 pmid: 1 publication: Journal of Experimental Botany publication_identifier: eissn: - 1460-2431 issn: - 0022-0957 publication_status: published publisher: Oxford University Press quality_controlled: '1' scopus_import: '1' status: public title: Distinct and redundant roles of the Arabidopsis OCTOPUS gene family in plant growth beyond phloem development tmp: image: /images/cc_by_nc.png legal_code_url: https://creativecommons.org/licenses/by-nc/4.0/legalcode name: Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) short: CC BY-NC (4.0) type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 76 year: '2025' ... --- OA_place: publisher _id: '19395' abstract: - lang: eng text: "Plant growth and development rely significantly on phytohormones, with auxin serving as a master regulator, orchestrating processes from embryogenesis to organogenesis, vascular patterning, and environmental adaptation. Since its conceptual proposition by Charles Darwin in 1880 as an endogenous chemical signal influencing phototropism in grass, auxin has captivated scientists seeking to understand how such a small molecule exerts a profound influence on plant development.\r\nOne particularly fascinating aspect of auxin function is its ability to self-organize its transport. Through a feedback mechanism between auxin perception and directional transport—primarily mediated by PIN auxin transporters—auxin establishes narrow transport channels. This phenomenon, known as auxin canalization, is fundamental to vascular formation, regeneration, and other key developmental processes. Despite advances in our understanding, driven by experimental studies and computational models, auxin canalization remains an enigma, with many unanswered questions.\r\nLike other hormones, auxin functions through intricate signaling pathways. It operates through at least two distinct signaling mechanisms: the well-characterized canonical pathway and the less understood non-canonical pathway. While significant progress has been made in elucidating the canonical pathway, the non-canonical mechanisms remain less defined and require further investigation.\r\nIn this study, we revisit the non-canonical auxin signaling pathway mediated by the cell-surface complex Auxin Binding Protein 1-Transmembrane Kinase 1 (ABP1-TMK1), with a particular focus on its downstream phosphorylation events. We reveal that this auxin-mediated phosphorylation is conserved across the green lineage, underscoring its fundamental role in plant development. We explore key phosphorylation targets, particularly PIN2, which is essential for root gravitropism. To further understand TMK1’s role in diverse developmental processes, we identified and investigated its interactors as potential co-receptors or regulatory components within its signaling network.\r\nGiven the previously established role of ABP1-TMK1 in auxin canalization, we sought to further investigate this process and identified several TMK1 interactors also involved in this intricate mechanism.\r\nThese findings provide new insights into the complex regulation of auxin canalization, highlighting a broader and more interconnected signaling framework than previously understood." acknowledged_ssus: - _id: LifeSc - _id: Bio acknowledgement: I would like to acknowledge the facilities at ISTA, particularly LSF, IOF, and, of course, the plant facility, for providing the necessary resources for my research. alternative_title: - ISTA Thesis article_processing_charge: No author: - first_name: Aline full_name: Monzer, Aline id: 2DB5D88C-D7B3-11E9-B8FD-7907E6697425 last_name: Monzer citation: ama: 'Monzer A. Cell-surface auxin signaling: Linking molecular pathways to plant development. 2025. doi:10.15479/AT-ISTA-19395' apa: 'Monzer, A. (2025). Cell-surface auxin signaling: Linking molecular pathways to plant development. Institute of Science and Technology Austria. https://doi.org/10.15479/AT-ISTA-19395' chicago: 'Monzer, Aline. “Cell-Surface Auxin Signaling: Linking Molecular Pathways to Plant Development.” Institute of Science and Technology Austria, 2025. https://doi.org/10.15479/AT-ISTA-19395.' ieee: 'A. Monzer, “Cell-surface auxin signaling: Linking molecular pathways to plant development,” Institute of Science and Technology Austria, 2025.' ista: 'Monzer A. 2025. Cell-surface auxin signaling: Linking molecular pathways to plant development. Institute of Science and Technology Austria.' mla: 'Monzer, Aline. Cell-Surface Auxin Signaling: Linking Molecular Pathways to Plant Development. Institute of Science and Technology Austria, 2025, doi:10.15479/AT-ISTA-19395.' short: 'A. Monzer, Cell-Surface Auxin Signaling: Linking Molecular Pathways to Plant Development, Institute of Science and Technology Austria, 2025.' corr_author: '1' date_created: 2025-03-12T14:25:42Z date_published: 2025-03-13T00:00:00Z date_updated: 2026-10-15T08:06:16Z day: '13' ddc: - '580' degree_awarded: PhD department: - _id: GradSch - _id: JiFr doi: 10.15479/AT-ISTA-19395 doi_confirm: '1' file: - access_level: open_access checksum: 9a3dd03bb4ec6b9907a325c3c4e8a1d7 content_type: application/pdf creator: amonzer date_created: 2025-03-12T14:14:49Z date_updated: 2025-03-12T14:14:49Z file_id: '19396' file_name: Final Thesis Aline Monzer.pdf file_size: 13119670 relation: main_file success: 1 - access_level: closed checksum: a353ce1ee2eabce37bca35499e76dbf1 content_type: application/vnd.openxmlformats-officedocument.wordprocessingml.document creator: amonzer date_created: 2025-03-12T14:15:19Z date_updated: 2025-04-01T07:55:27Z file_id: '19397' file_name: Thesis Aline.docx file_size: 13774837 relation: source_file file_date_updated: 2025-04-01T07:55:27Z fulldoi: https://doi.org/10.15479/AT-ISTA-19395 has_accepted_license: '1' language: - iso: eng month: '03' oa: 1 oa_version: Published Version page: '160' publication_identifier: eisbn: - 978-3-99078-054-1 eissn: - 2663-337X publication_status: published publisher: Institute of Science and Technology Austria related_material: record: - id: '12291' relation: part_of_dissertation status: public - id: '19399' relation: part_of_dissertation status: public - id: '19398' relation: part_of_dissertation status: public - id: '14826' relation: part_of_dissertation status: public status: public supervisor: - first_name: Jiří full_name: Friml, Jiří id: 4159519E-F248-11E8-B48F-1D18A9856A87 last_name: Friml orcid: 0000-0002-8302-7596 title: 'Cell-surface auxin signaling: Linking molecular pathways to plant development' type: dissertation user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9 year: '2025' ... --- OA_place: publisher OA_type: free access _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. doi:10.52202/085713-3769' 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. https://doi.org/10.52202/085713-3769' 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. https://doi.org/10.52202/085713-3769. 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, doi:10.52202/085713-3769. 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: 2026-10-15T09:17:34Z day: '15' ddc: - '000' department: - _id: FrLo doi: 10.52202/085713-3769 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 fulldoi: https://doi.org/10.52202/085713-3769 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: free access _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. doi:10.52202/085713-2479' 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. https://doi.org/10.52202/085713-2479' 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. https://doi.org/10.52202/085713-2479. 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, doi:10.52202/085713-2479. 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: 2026-10-15T09:29:52Z day: '15' ddc: - '000' department: - _id: FrLo - _id: SyCr doi: 10.52202/085713-2479 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 fulldoi: https://doi.org/10.52202/085713-2479 has_accepted_license: '1' intvolume: ' 38' language: - iso: eng month: '12' oa: 1 oa_version: Published Version project: - _id: a392d8f0-b034-11f1-b88e-d3025c6734f6 grant_number: COE12 name: Bilateral Artificial Intelligence (Locatello) publication: 39th Annual Conference on Neural Information Processing Systems publication_identifier: eissn: - 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: free access _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. doi:10.52202/085713-3752' 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. https://doi.org/10.52202/085713-3752' 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. https://doi.org/10.52202/085713-3752.' 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, doi:10.52202/085713-3752.' 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: 2026-10-15T09:26:57Z day: '15' ddc: - '000' department: - _id: FrLo doi: 10.52202/085713-3752 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 fulldoi: https://doi.org/10.52202/085713-3752 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: eissn: - 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. doi:10.52202/085713-1444' 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. https://doi.org/10.52202/085713-1444' 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. https://doi.org/10.52202/085713-1444. 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, doi:10.52202/085713-1444. 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: 2026-10-15T09:31:39Z day: '15' ddc: - '000' department: - _id: FrLo doi: 10.52202/085713-1444 external_id: arxiv: - '2505.17708' fulldoi: https://doi.org/10.52202/085713-1444 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 project: - _id: a392d8f0-b034-11f1-b88e-d3025c6734f6 grant_number: COE12 name: Bilateral Artificial Intelligence (Locatello) publication: 39th Annual Conference on Neural Information Processing Systems publication_identifier: eissn: - 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: publisher OA_type: hybrid _id: '18631' abstract: - lang: eng text: Within the established framework of structure formation, galaxies start as systems of low stellar mass and gradually grow into far more massive galaxies. The existence of massive galaxies in the first billion years of the Universe, as suggested by recent observations, seems to challenge this model, as such galaxies would require highly efficient conversion of baryons into stars. An even greater challenge in this epoch is the existence of massive galaxies that have already ceased forming stars. However, robust detections of early massive quiescent galaxies have been challenging due to the coarse wavelength sampling of photometric surveys. Here we report the spectroscopic confirmation with the James Webb Space Telescope of the quiescent galaxy RUBIES-EGS-QG-1 at redshift z = 4.90, 1.2 billion years after the Big Bang. Deep stellar absorption features in the spectrum reveal that the stellar mass of the galaxy of 1011 M⊙ formed in a short 200 Myr burst of star formation, after which star formation activity dropped rapidly and persistently. According to current galaxy formation models, systems with such rapid stellar mass growth and early quenching are too rare to plausibly occur in the small area probed spectroscopically with JWST. Instead, the discovery of RUBIES-EGS-QG-1 implies that early massive quiescent galaxies can be quenched earlier or exhaust gas available for star formation more efficiently than assumed at present. acknowledgement: We thank V. Buat, D. Burgarella and J. Zavala for sharing their NOEMA data and constraints on the dust-obscured star formation of RUBIES-EGS-QG-1. This work is partially based on observations carried out under project number W20CK with the IRAM NOEMA Interferometer. IRAM is supported by INSU/CNRS (France), MPG (Germany) and IGN (Spain). We thank C. Lagos for providing measurements from the SHARK simulation. This research was supported by the International Space Science Institute (ISSI) in Bern, through ISSI International Team Project No. 562. M.V.M., J.L. and B.W. acknowledge funding support from NASA through JWST-GO-4233. The Cosmic Dawn Center is funded by the Danish National Research Foundation (Grant No. DNRF140 to G.B., P.A.O. and K.E.W.). This work has received funding from the Swiss State Secretariat for Education, Research and Innovation (Contract No. MB22.00072) and the Swiss National Science Foundation (Project Grant No. 200020_207349 to P.A.O.). Support for this work was provided by the Brinson Foundation through a Brinson Prize Fellowship grant (D.J.S.). K.A.S. is a NHFP Hubble Fellow. Support for this work was provided by NASA through the NASA Hubble Fellowship Grant No. HST-HF2-51515.001-A awarded by the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Incorporated, under NASA contract NAS 5-26555 (R.P.N.). This work is based on observations made with the NASA/ESA/CSA JWST. The data were obtained from the Mikulski Archive for Space Telescopes at the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS 5-03127 for JWST. The observations in this work are associated with programmes ERS-1345, GO-2234, DDT-2750 and GO-4233. We gratefully acknowledge the CEERS and DDT-2750 teams for developing their observing programme with a zero-exclusive-access period. Open access funding provided by Max Planck Society. article_processing_charge: Yes (via OA deal) article_type: original author: - first_name: Anna full_name: De Graaff, Anna last_name: De Graaff - first_name: David J. full_name: Setton, David J. last_name: Setton - first_name: Gabriel full_name: Brammer, Gabriel last_name: Brammer - first_name: Sam full_name: Cutler, Sam last_name: Cutler - first_name: Katherine A. full_name: Suess, Katherine A. last_name: Suess - first_name: Ivo full_name: Labbé, Ivo last_name: Labbé - first_name: Joel full_name: Leja, Joel last_name: Leja - first_name: Andrea full_name: Weibel, Andrea last_name: Weibel - first_name: Michael V. full_name: Maseda, Michael V. last_name: Maseda - first_name: Katherine E. full_name: Whitaker, Katherine E. last_name: Whitaker - first_name: Rachel full_name: Bezanson, Rachel last_name: Bezanson - first_name: Leindert A. full_name: Boogaard, Leindert A. last_name: Boogaard - first_name: Nikko J. full_name: Cleri, Nikko J. last_name: Cleri - first_name: Gabriella full_name: De Lucia, Gabriella last_name: De Lucia - first_name: Marijn full_name: Franx, Marijn last_name: Franx - first_name: Jenny E. full_name: Greene, Jenny E. last_name: Greene - first_name: Michaela full_name: Hirschmann, Michaela last_name: Hirschmann - first_name: Jorryt J full_name: Matthee, Jorryt J id: 7439a258-f3c0-11ec-9501-9df22fe06720 last_name: Matthee orcid: 0000-0003-2871-127X - first_name: Ian full_name: Mcconachie, Ian last_name: Mcconachie - first_name: Rohan P. full_name: Naidu, Rohan P. last_name: Naidu - first_name: Pascal A. full_name: Oesch, Pascal A. last_name: Oesch - first_name: Sedona H. full_name: Price, Sedona H. last_name: Price - first_name: Hans Walter full_name: Rix, Hans Walter last_name: Rix - first_name: Francesco full_name: Valentino, Francesco last_name: Valentino - first_name: Bingjie full_name: Wang, Bingjie last_name: Wang - first_name: Christina C. full_name: Williams, Christina C. last_name: Williams citation: ama: De Graaff A, Setton DJ, Brammer G, et al. Efficient formation of a massive quiescent galaxy at redshift 4.9. Nature Astronomy. 2025;9:280-292. doi:10.1038/s41550-024-02424-3 apa: De Graaff, A., Setton, D. J., Brammer, G., Cutler, S., Suess, K. A., Labbé, I., … Williams, C. C. (2025). Efficient formation of a massive quiescent galaxy at redshift 4.9. Nature Astronomy. Springer Nature. https://doi.org/10.1038/s41550-024-02424-3 chicago: De Graaff, Anna, David J. Setton, Gabriel Brammer, Sam Cutler, Katherine A. Suess, Ivo Labbé, Joel Leja, et al. “Efficient Formation of a Massive Quiescent Galaxy at Redshift 4.9.” Nature Astronomy. Springer Nature, 2025. https://doi.org/10.1038/s41550-024-02424-3. ieee: A. De Graaff et al., “Efficient formation of a massive quiescent galaxy at redshift 4.9,” Nature Astronomy, vol. 9. Springer Nature, pp. 280–292, 2025. ista: De Graaff A, Setton DJ, Brammer G, Cutler S, Suess KA, Labbé I, Leja J, Weibel A, Maseda MV, Whitaker KE, Bezanson R, Boogaard LA, Cleri NJ, De Lucia G, Franx M, Greene JE, Hirschmann M, Matthee JJ, Mcconachie I, Naidu RP, Oesch PA, Price SH, Rix HW, Valentino F, Wang B, Williams CC. 2025. Efficient formation of a massive quiescent galaxy at redshift 4.9. Nature Astronomy. 9, 280–292. mla: De Graaff, Anna, et al. “Efficient Formation of a Massive Quiescent Galaxy at Redshift 4.9.” Nature Astronomy, vol. 9, Springer Nature, 2025, pp. 280–92, doi:10.1038/s41550-024-02424-3. short: A. De Graaff, D.J. Setton, G. Brammer, S. Cutler, K.A. Suess, I. Labbé, J. Leja, A. Weibel, M.V. Maseda, K.E. Whitaker, R. Bezanson, L.A. Boogaard, N.J. Cleri, G. De Lucia, M. Franx, J.E. Greene, M. Hirschmann, J.J. Matthee, I. Mcconachie, R.P. Naidu, P.A. Oesch, S.H. Price, H.W. Rix, F. Valentino, B. Wang, C.C. Williams, Nature Astronomy 9 (2025) 280–292. das_tickbox: '1' dataavailabilitystatement: The unprocessed JWST data are available through the Mikulski Archive for Space Telescopes. Reduced data from JWST underlying this work are publicly available in the DJA (https://dawn-cph.github.io/dja/), as described in refs. 9,46. date_created: 2024-12-08T23:01:56Z date_published: 2025-02-01T00:00:00Z date_updated: 2026-10-15T09:40:28Z day: '01' ddc: - '520' department: - _id: JoMa doi: 10.1038/s41550-024-02424-3 external_id: isi: - '001420347200001' pmid: - '39990236' file: - access_level: open_access checksum: fb9109951dfe72f08c04c72cd7cfba69 content_type: application/pdf creator: dernst date_created: 2025-04-16T08:53:59Z date_updated: 2025-04-16T08:53:59Z file_id: '19574' file_name: 2025_NatureAstronomy_deGraaff.pdf file_size: 2034513 relation: main_file success: 1 file_date_updated: 2025-04-16T08:53:59Z fulldoi: https://doi.org/10.1038/s41550-024-02424-3 has_accepted_license: '1' intvolume: ' 9' isi: 1 language: - iso: eng month: '02' oa: 1 oa_version: Published Version page: 280-292 pmid: 1 publication: Nature Astronomy publication_identifier: eissn: - 2397-3366 publication_status: published publisher: Springer Nature quality_controlled: '1' researchdata_availability: yes scopus_import: '1' status: public supplementarymaterial: yes title: Efficient formation of a massive quiescent galaxy at redshift 4.9 tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345 volume: 9 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. doi:10.52202/085713-3125' 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. https://doi.org/10.52202/085713-3125' 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. https://doi.org/10.52202/085713-3125. 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, doi:10.52202/085713-3125. 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: 2026-10-15T09:32:34Z day: '01' ddc: - '000' department: - _id: FrLo doi: 10.52202/085713-3125 external_id: arxiv: - '2410.04525' fulldoi: https://doi.org/10.52202/085713-3125 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 project: - _id: a392d8f0-b034-11f1-b88e-d3025c6734f6 grant_number: COE12 name: Bilateral Artificial Intelligence (Locatello) publication: 39th Annual Conference on Neural Information Processing Systems publication_identifier: eissn: - 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: free access _id: '22823' abstract: - lang: eng text: This position paper argues that setting the privacy budget in differential privacy should not be viewed as an important limitation of differential privacy compared to alternative methods for privacy-preserving machine learning. The so-called problem of interpreting the privacy budget is often presented as a major hindrance to the wider adoption of differential privacy in real-world deployments and is sometimes used to promote alternative mitigation techniques for data protection. We believe this misleads decision-makers into choosing unsafe methods. We argue that the difficulty in interpreting privacy budgets does not stem from the definition of differential privacy itself, but from the intrinsic difficulty of estimating privacy risks in context, a challenge that any rigorous method for privacy risk assessment face. Moreover, we claim that any sound method for estimating privacy risks should, given the current state of research, be expressible within the differential privacy framework or justify why it cannot. acknowledgement: "This research was funded in whole by the Austrian Science Fund (FWF) 10.55776/COE12. I thank\r\nAlberto Naibo for the discussion and his invitation to \"Logique, droit, IA : penser les algorithmes\"\r\ncolloquium. I thank Simone Bombari for the discussions. I thank EurIPS for the active poster session." alternative_title: - Advances in Neural Information Processing Systems article_processing_charge: No author: - first_name: Edwige Audrey Lucienne full_name: Cyffers, Edwige Audrey Lucienne id: 20d4c299-977a-11ef-ae55-98b15ac64a57 last_name: Cyffers citation: ama: 'Cyffers EAL. Setting ε is not the issue in differential privacy. In: 39th Conference on Neural Information Processing Systems. Vol 38. Neural Information Processing Systems Foundation; 2025:159016-159028. doi:10.52202/085713-4798' apa: 'Cyffers, E. A. L. (2025). Setting ε is not the issue in differential privacy. In 39th Conference on Neural Information Processing Systems (Vol. 38, pp. 159016–159028). San Diego, CA, United States: Neural Information Processing Systems Foundation. https://doi.org/10.52202/085713-4798' chicago: Cyffers, Edwige Audrey Lucienne. “Setting ε Is Not the Issue in Differential Privacy.” In 39th Conference on Neural Information Processing Systems, 38:159016–28. Neural Information Processing Systems Foundation, 2025. https://doi.org/10.52202/085713-4798. ieee: E. A. L. Cyffers, “Setting ε is not the issue in differential privacy,” in 39th Conference on Neural Information Processing Systems, San Diego, CA, United States, 2025, vol. 38, pp. 159016–159028. ista: 'Cyffers EAL. 2025. Setting ε is not the issue in differential privacy. 39th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems, Advances in Neural Information Processing Systems, vol. 38, 159016–159028.' mla: Cyffers, Edwige Audrey Lucienne. “Setting ε Is Not the Issue in Differential Privacy.” 39th Conference on Neural Information Processing Systems, vol. 38, Neural Information Processing Systems Foundation, 2025, pp. 159016–28, doi:10.52202/085713-4798. short: E.A.L. Cyffers, in:, 39th Conference on Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2025, pp. 159016–159028. 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: '0' date_created: 2026-09-06T22:01:59Z date_published: 2025-12-02T00:00:00Z date_updated: 2026-10-15T09:34:50Z day: '02' department: - _id: ChLa doi: 10.52202/085713-4798 fulldoi: https://doi.org/10.52202/085713-4798 intvolume: ' 38' language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.52202/085713-4798 month: '12' oa: 1 oa_version: Published Version page: 159016-159028 project: - _id: d8f03aaa-b035-11f1-8588-d5147fa879e0 grant_number: COE12 name: Bilateral Artificial Intelligence (Lampert) publication: 39th Conference on Neural Information Processing Systems publication_identifier: eissn: - 1049-5258 isbn: - '9798331338275' publication_status: published publisher: Neural Information Processing Systems Foundation quality_controlled: '1' researchdata_availability: no scopus_import: '1' status: public supplementarymaterial: yes title: Setting ε is not the issue in differential privacy type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 38 year: '2025' ...