--- OA_place: publisher _id: '22735' acknowledged_ssus: - _id: M-Shop - _id: PreCl - _id: Bio acknowledgement: "This project was supported by the following funding agencies: ERC under the European\r\nUnion's Horizon 2020 research and innovation program (ERC Advanced Grants No 692692\r\n“GIANTSYN” and 101199096 “CA3-SYNGRAM” to P.J.), the Fonds zur Förderung der\r\nwissenschaftlichen Forschung (P 36232-B, stand-alone grant, PAT 4178023, principal\r\ninvestigator project, and 10.55776/CoE 16 “GABA neurons” to P.J.), and the European Union’s\r\nHorizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant\r\nagreement (No 101034413, to K.L.)." alternative_title: - ISTA Thesis article_processing_charge: No author: - first_name: Peipeng full_name: Lin, Peipeng id: 7E3060D0-A92C-11E9-A326-26C8E5697425 last_name: Lin citation: ama: 'Lin P. Calibrating the teacher synapse: Mechanisms and functional significance of presynaptic inhibition at hippocampal mossy fiber synapses. 2026. doi:10.15479/AT-ISTA-22735' apa: 'Lin, P. (2026). Calibrating the teacher synapse: Mechanisms and functional significance of presynaptic inhibition at hippocampal mossy fiber synapses. Institute of Science and Technology Austria. https://doi.org/10.15479/AT-ISTA-22735' chicago: 'Lin, Peipeng. “Calibrating the Teacher Synapse: Mechanisms and Functional Significance of Presynaptic Inhibition at Hippocampal Mossy Fiber Synapses.” Institute of Science and Technology Austria, 2026. https://doi.org/10.15479/AT-ISTA-22735.' ieee: 'P. Lin, “Calibrating the teacher synapse: Mechanisms and functional significance of presynaptic inhibition at hippocampal mossy fiber synapses,” Institute of Science and Technology Austria, 2026.' ista: 'Lin P. 2026. Calibrating the teacher synapse: Mechanisms and functional significance of presynaptic inhibition at hippocampal mossy fiber synapses. Institute of Science and Technology Austria.' mla: 'Lin, Peipeng. Calibrating the Teacher Synapse: Mechanisms and Functional Significance of Presynaptic Inhibition at Hippocampal Mossy Fiber Synapses. Institute of Science and Technology Austria, 2026, doi:10.15479/AT-ISTA-22735.' short: 'P. Lin, Calibrating the Teacher Synapse: Mechanisms and Functional Significance of Presynaptic Inhibition at Hippocampal Mossy Fiber Synapses, Institute of Science and Technology Austria, 2026.' corr_author: '1' das_tickbox: '0' date_created: 2026-08-18T15:23:41Z date_published: 2026-08-25T00:00:00Z date_updated: 2026-09-16T07:39:42Z day: '25' ddc: - '571' - '573' degree_awarded: PhD department: - _id: GradSch - _id: PeJo doi: 10.15479/AT-ISTA-22735 doi_confirm: '1' ec_funded: 1 file: - access_level: closed checksum: 13cc7ead72aad90a134f310b531c73cd content_type: application/pdf creator: plin date_created: 2026-08-26T10:09:48Z date_updated: 2026-08-26T10:09:48Z embargo: 2027-09-01 embargo_to: open_access file_id: '22765' file_name: 2026_Lin_Peipeng_Thesis.pdf file_size: 6376229 relation: main_file - access_level: closed checksum: 8c9c1445a7df284377be1a8c9dadd7c5 content_type: application/vnd.openxmlformats-officedocument.wordprocessingml.document creator: plin date_created: 2026-08-26T10:09:53Z date_updated: 2026-08-26T10:09:53Z file_id: '22766' file_name: 2026_Lin_Peipeng_Thesis.docx file_size: 17681883 relation: source_file file_date_updated: 2026-08-26T10:09:53Z fulldoi: https://doi.org/10.15479/AT-ISTA-22735 has_accepted_license: '1' language: - iso: eng license: https://creativecommons.org/licenses/by-nc-nd/4.0/ month: '08' oa_version: Published Version page: '88' project: - _id: 25B7EB9E-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '692692' name: Biophysics and circuit function of a giant cortical glutamatergic synapse - _id: e62b56fe-ab3c-11f0-94c7-d181dd352b3b grant_number: '101199096' name: Synaptic mechanisms of engram storage and retrieval in CA3 hippocampal microcircuits - _id: bd88be38-d553-11ed-ba76-81d5a70a6ef5 grant_number: P36232 name: Mechanisms of GABA release in hippocampal circuits - _id: 8d9195e9-16d5-11f0-9cad-d075be887a1e grant_number: PAT 4178023 name: Synaptic networks of human brain - _id: fc2ed2f7-9c52-11eb-aca3-c01059dda49c call_identifier: H2020 grant_number: '101034413' name: 'IST-BRIDGE: International postdoctoral program' - _id: 0a6c8641-b036-11f1-bacf-e4eec62b5bb4 grant_number: COE16 name: Neuronal circuits in health and disease (Jonas) publication_identifier: isbn: - 978-3-99078-088-6 issn: - 2663-337X publication_status: published publisher: Institute of Science and Technology Austria researchdata_availability: upon request status: public supervisor: - first_name: Peter M full_name: Jonas, Peter M id: 353C1B58-F248-11E8-B48F-1D18A9856A87 last_name: Jonas orcid: 0000-0001-5001-4804 supplementarymaterial: yes title: 'Calibrating the teacher synapse: Mechanisms and functional significance of presynaptic inhibition at hippocampal mossy fiber synapses' tmp: image: /images/cc_by_nc_nd.png legal_code_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode name: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) short: CC BY-NC-ND (4.0) type: dissertation user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2026' ... --- OA_embargo: '18' OA_place: publisher _id: '22775' acknowledged_ssus: - _id: Bio - _id: PreCl - _id: M-Shop - _id: LifeSc alternative_title: - ISTA Thesis article_processing_charge: No author: - first_name: Silvia full_name: Jamrichova, Silvia id: F0EA6804-AA27-11E9-8613-C0F7E5697425 last_name: Jamrichova orcid: 0009-0003-9929-8221 citation: ama: Jamrichova S. Timing and strength of synaptic transmission at hippocampal mossy fiber synapses in mice and humans. 2026. doi:10.15479/AT-ISTA-22775 apa: Jamrichova, S. (2026). Timing and strength of synaptic transmission at hippocampal mossy fiber synapses in mice and humans. Institute of Science and Technology Austria. https://doi.org/10.15479/AT-ISTA-22775 chicago: Jamrichova, Silvia. “Timing and Strength of Synaptic Transmission at Hippocampal Mossy Fiber Synapses in Mice and Humans.” Institute of Science and Technology Austria, 2026. https://doi.org/10.15479/AT-ISTA-22775. ieee: S. Jamrichova, “Timing and strength of synaptic transmission at hippocampal mossy fiber synapses in mice and humans,” Institute of Science and Technology Austria, 2026. ista: Jamrichova S. 2026. Timing and strength of synaptic transmission at hippocampal mossy fiber synapses in mice and humans. Institute of Science and Technology Austria. mla: Jamrichova, Silvia. Timing and Strength of Synaptic Transmission at Hippocampal Mossy Fiber Synapses in Mice and Humans. Institute of Science and Technology Austria, 2026, doi:10.15479/AT-ISTA-22775. short: S. Jamrichova, Timing and Strength of Synaptic Transmission at Hippocampal Mossy Fiber Synapses in Mice and Humans, Institute of Science and Technology Austria, 2026. corr_author: '1' date_created: 2026-09-03T08:06:58Z date_published: 2026-09-03T00:00:00Z date_updated: 2026-09-16T08:13:41Z day: '03' ddc: - '570' degree_awarded: PhD department: - _id: GradSch - _id: PeJo doi: 10.15479/AT-ISTA-22775 doi_confirm: '1' ec_funded: 1 file: - access_level: closed checksum: d9a6fd39a0b6343c4473901f9323f127 content_type: application/pdf creator: cchlebak date_created: 2026-09-08T09:01:22Z date_updated: 2026-09-08T09:01:22Z embargo: 2028-03-08 embargo_to: open_access file_id: '22850' file_name: 2026_Jamrichova_Silvia_Thesis.pdf file_size: 8968078 relation: main_file - access_level: closed checksum: 02b728c9157f88e392b69e94877889f0 content_type: application/vnd.openxmlformats-officedocument.wordprocessingml.document creator: cchlebak date_created: 2026-09-08T09:02:52Z date_updated: 2026-09-08T09:02:52Z file_id: '22851' file_name: 2026_Jamrichova_Silvia_Thesis.docx file_size: 17338630 relation: source_file file_date_updated: 2026-09-08T09:02:52Z fulldoi: https://doi.org/10.15479/AT-ISTA-22775 has_accepted_license: '1' language: - iso: eng license: https://creativecommons.org/licenses/by/4.0/ month: '09' oa_version: Published Version page: '153' project: - _id: 25B7EB9E-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '692692' name: Biophysics and circuit function of a giant cortical glutamatergic synapse - _id: e62b56fe-ab3c-11f0-94c7-d181dd352b3b grant_number: '101199096' name: Synaptic mechanisms of engram storage and retrieval in CA3 hippocampal microcircuits - _id: bd88be38-d553-11ed-ba76-81d5a70a6ef5 grant_number: P36232 name: Mechanisms of GABA release in hippocampal circuits - _id: 8d9195e9-16d5-11f0-9cad-d075be887a1e grant_number: PAT 4178023 name: Synaptic networks of human brain - _id: 25C5A090-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z00312 name: Synaptic communication in neuronal microcircuits - _id: 0a6c8641-b036-11f1-bacf-e4eec62b5bb4 grant_number: COE16 name: Neuronal circuits in health and disease (Jonas) publication_identifier: isbn: - 978-3-99078-085-5 issn: - 2663-337X publication_status: published publisher: Institute of Science and Technology Austria researchdata_availability: upon request status: public supervisor: - first_name: Peter M full_name: Jonas, Peter M id: 353C1B58-F248-11E8-B48F-1D18A9856A87 last_name: Jonas orcid: 0000-0001-5001-4804 supplementarymaterial: no title: Timing and strength of synaptic transmission at hippocampal mossy fiber synapses in mice and humans 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: 8b945eb4-e2f2-11eb-945a-df72226e66a9 year: '2026' ... --- OA_place: repository OA_type: green _id: '22923' abstract: - lang: eng text: "We study the sensitivity of the eigenvectors of random matrices, showing that even small perturbations make the eigenvectors almost orthogonal. More precisely, we consider two deformed Wigner matrices \U0001D44A +\U0001D4371, \U0001D44A +\U0001D4372 and show that their bulk eigenvectors become asymptotically orthogonal as soon as Tr⁡(\U0001D4371−\U0001D4372)2 ≫1, or their respective energies are separated on a scale much bigger than the local eigenvalue spacing. Furthermore, we show that quadratic forms of eigenvectors of \U0001D44A +\U0001D4371, \U0001D44A +\U0001D4372 with any deterministic matrix \U0001D434 ∈\U0001D402\U0001D441×\U0001D441 in a specific subspace of codimension one are of size \U0001D441−1/2. This proves a generalization of the eigenstate thermalization hypothesis to eigenvectors belonging to two different spectral families." acknowledgement: L. Erdős, J. Henheik and O. Kolupaiev were supported by the ERC Advanced Grant “RMTBeyond” No. 101020331. G. Cipolloni is partially supported by the MUR Excellence Department Project MatMod@TOV awarded to the Department of Mathematics, University of Rome Tor Vergata, CUP E83C18000100006. article_processing_charge: No article_type: original arxiv: 1 author: - first_name: Giorgio full_name: Cipolloni, Giorgio id: 42198EFA-F248-11E8-B48F-1D18A9856A87 last_name: Cipolloni orcid: 0000-0002-4901-7992 - first_name: László full_name: Erdös, László id: 4DBD5372-F248-11E8-B48F-1D18A9856A87 last_name: Erdös orcid: 0000-0001-5366-9603 - first_name: Sven Joscha full_name: Henheik, Sven Joscha id: 31d731d7-d235-11ea-ad11-b50331c8d7fb last_name: Henheik orcid: 0000-0003-1106-327X - first_name: Oleksii full_name: Kolupaiev, Oleksii id: 149b70d4-896a-11ed-bdf8-8c63fd44ca61 last_name: Kolupaiev orcid: 0000-0003-1491-4623 citation: ama: Cipolloni G, Erdös L, Henheik SJ, Kolupaiev O. Eigenvector decorrelation for random matrices. Annals of Applied Probability. 2026;36(4):3707-3756. doi:10.1214/26-AAP2318 apa: Cipolloni, G., Erdös, L., Henheik, S. J., & Kolupaiev, O. (2026). Eigenvector decorrelation for random matrices. Annals of Applied Probability. Institute of Mathematical Statistics. https://doi.org/10.1214/26-AAP2318 chicago: Cipolloni, Giorgio, László Erdös, Sven Joscha Henheik, and Oleksii Kolupaiev. “Eigenvector Decorrelation for Random Matrices.” Annals of Applied Probability. Institute of Mathematical Statistics, 2026. https://doi.org/10.1214/26-AAP2318. ieee: G. Cipolloni, L. Erdös, S. J. Henheik, and O. Kolupaiev, “Eigenvector decorrelation for random matrices,” Annals of Applied Probability, vol. 36, no. 4. Institute of Mathematical Statistics, pp. 3707–3756, 2026. ista: Cipolloni G, Erdös L, Henheik SJ, Kolupaiev O. 2026. Eigenvector decorrelation for random matrices. Annals of Applied Probability. 36(4), 3707–3756. mla: Cipolloni, Giorgio, et al. “Eigenvector Decorrelation for Random Matrices.” Annals of Applied Probability, vol. 36, no. 4, Institute of Mathematical Statistics, 2026, pp. 3707–56, doi:10.1214/26-AAP2318. short: G. Cipolloni, L. Erdös, S.J. Henheik, O. Kolupaiev, Annals of Applied Probability 36 (2026) 3707–3756. corr_author: '1' das_tickbox: '0' date_created: 2026-09-13T22:01:54Z date_published: 2026-08-01T00:00:00Z date_updated: 2026-09-16T10:00:54Z day: '01' department: - _id: LaEr - _id: GradSch doi: 10.1214/26-AAP2318 ec_funded: 1 external_id: arxiv: - '2410.10718' fulldoi: https://doi.org/10.1214/26-AAP2318 intvolume: ' 36' issue: '4' keyword: - characteristic flow - Davis–Kahan theorem - Eigenstate thermalization - Eigenvector perturbation theory - Local law - zigzag strategy language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.48550/arXiv.2410.10718 mathsc: - 60B20 - 82C10 month: '08' oa: 1 oa_version: Preprint page: 3707-3756 project: - _id: 62796744-2b32-11ec-9570-940b20777f1d call_identifier: H2020 grant_number: '101020331' name: Random matrices beyond Wigner-Dyson-Mehta publication: Annals of Applied Probability publication_identifier: issn: - 1050-5164 publication_status: published publisher: Institute of Mathematical Statistics quality_controlled: '1' related_material: record: - id: '19546' relation: earlier_version status: public researchdata_availability: no scopus_import: '1' status: public supplementarymaterial: yes title: Eigenvector decorrelation for random matrices type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 36 year: '2026' ... --- OA_place: publisher OA_type: hybrid _id: '22925' abstract: - lang: eng text: Hybridization Chain Reaction (HCR) enables highly sensitive and multiplexed detection of mRNA with subcellular spatial resolution. It employs fluorophore-tagged DNA hairpins that self-assemble on target-bound probe pairs, amplifying the signal without enzymatic reactions. Here, we describe a protocol for performing HCR fluorescence in situ hybridization (FISH) on Xenopus tissue sections. We also outline a semi-automated image analysis pipeline that enables per-cell quantification of probe expression and co-localization. This method provides a robust and quantitative approach for visualizing gene expression patterns in situ. acknowledgement: "This work was supported by a Horizon Europe ERC Starting Grant\r\nNumber 101041551 (L.B.S., D.V., S.P.), Special Research Program\r\n(SFB) of the Austrian Science Fund (FWF) F7814-B (L.B.S., S.P.),\r\nAustrian Science Fund (FWF) 10.55776/COE16 (L.B.S.), FTI\r\nStrategy Lower Austria Dissertation Grant Number FT121-D-046\r\n(D.V.), and Austrian Academy of Sciences DOC Fellowship 27229\r\n(S.P.). We also thank the Imaging & Optics and Scientific Computing Facilities at ISTA for their support in developing the quantification pipeline." alternative_title: - Methods in Molecular Biology article_processing_charge: No author: - first_name: David full_name: Vijatovic, David id: cf391e77-ec3c-11ea-a124-d69323410b58 last_name: Vijatovic orcid: 0000-0002-5494-0941 - first_name: Stavros full_name: Papadopoulos, Stavros id: 40606b92-f128-11eb-9611-bf66a98cfa5c last_name: Papadopoulos - first_name: Marco full_name: Dalla Vecchia, Marco id: 02a7a869-ff06-11ed-a87f-86649d6077e5 last_name: Dalla Vecchia - first_name: Lora Beatrice Jaeger full_name: Sweeney, Lora Beatrice Jaeger id: 56BE8254-C4F0-11E9-8E45-0B23E6697425 last_name: Sweeney orcid: 0000-0001-9242-5601 citation: ama: 'Vijatovic D, Papadopoulos S, Dalla Vecchia M, Sweeney LB. Fluorescent in situ mRNA hybridization (FISH) using Hybridization Chain Reaction (HCR) in Xenopus cryosections. In: Beck CW, ed. Xenopus. Vol 3049. MIMB. Springer; 2026:245-259. doi:10.1007/978-1-0716-5360-9_11' apa: Vijatovic, D., Papadopoulos, S., Dalla Vecchia, M., & Sweeney, L. B. (2026). Fluorescent in situ mRNA hybridization (FISH) using Hybridization Chain Reaction (HCR) in Xenopus cryosections. In C. W. Beck (Ed.), Xenopus (Vol. 3049, pp. 245–259). Springer. https://doi.org/10.1007/978-1-0716-5360-9_11 chicago: Vijatovic, David, Stavros Papadopoulos, Marco Dalla Vecchia, and Lora B. Sweeney. “Fluorescent in Situ MRNA Hybridization (FISH) Using Hybridization Chain Reaction (HCR) in Xenopus Cryosections.” In Xenopus, edited by Caroline W. Beck, 3049:245–59. MIMB. Springer, 2026. https://doi.org/10.1007/978-1-0716-5360-9_11. ieee: D. Vijatovic, S. Papadopoulos, M. Dalla Vecchia, and L. B. Sweeney, “Fluorescent in situ mRNA hybridization (FISH) using Hybridization Chain Reaction (HCR) in Xenopus cryosections,” in Xenopus, vol. 3049, C. W. Beck, Ed. Springer, 2026, pp. 245–259. ista: 'Vijatovic D, Papadopoulos S, Dalla Vecchia M, Sweeney LB. 2026.Fluorescent in situ mRNA hybridization (FISH) using Hybridization Chain Reaction (HCR) in Xenopus cryosections. In: Xenopus. Methods in Molecular Biology, vol. 3049, 245–259.' mla: Vijatovic, David, et al. “Fluorescent in Situ MRNA Hybridization (FISH) Using Hybridization Chain Reaction (HCR) in Xenopus Cryosections.” Xenopus, edited by Caroline W. Beck, vol. 3049, Springer, 2026, pp. 245–59, doi:10.1007/978-1-0716-5360-9_11. short: D. Vijatovic, S. Papadopoulos, M. Dalla Vecchia, L.B. Sweeney, in:, C.W. Beck (Ed.), Xenopus, Springer, 2026, pp. 245–259. corr_author: '1' das_tickbox: '0' date_created: 2026-09-13T22:01:55Z date_published: 2026-09-02T00:00:00Z date_updated: 2026-09-17T07:31:16Z day: '02' ddc: - '570' department: - _id: LoSw - _id: GradSch - _id: IAS doi: 10.1007/978-1-0716-5360-9_11 editor: - first_name: Caroline W. full_name: Beck, Caroline W. last_name: Beck external_id: pmid: - '42681228' file: - access_level: open_access checksum: e7a075a9ee1b91d5824f8f2b9b1f3c9b content_type: application/pdf creator: dernst date_created: 2026-09-17T07:28:53Z date_updated: 2026-09-17T07:28:53Z file_id: '22938' file_name: 2026_MIMB_Vijatovic.pdf file_size: 1004024 relation: main_file success: 1 file_date_updated: 2026-09-17T07:28:53Z fulldoi: https://doi.org/10.1007/978-1-0716-5360-9_11 has_accepted_license: '1' intvolume: ' 3049' keyword: - mRNA FISH - Hybridization chain reaction - In situ hybridization - Fluorescence microscopy language: - iso: eng month: '09' oa: 1 oa_version: Published Version page: 245-259 pmid: 1 project: - _id: ebb66355-77a9-11ec-83b8-b8ac210a4dae grant_number: '101041551' name: Development and Evolution of Tetrapod Motor Circuits - _id: 8da85f50-16d5-11f0-9cad-eab8b0ff6c9e grant_number: F7814 name: 'Stem Cell Modulation in Neural Development and Regeneration/ P14-Swim-to-limb transition: cell type to connection diversity' - _id: cf428362-b037-11f1-b015-8277a8a2f63d grant_number: COE16 name: Neuronal circuits in health and disease (Sweeney) - _id: bd73af52-d553-11ed-ba76-912049f0ac7a grant_number: FTI21-D-046 name: Development of V1 interneuron diversity during swim-to-walk transition of Xenopus metamorphosis - _id: 907b765e-16d5-11f0-9cad-fef108a945b1 grant_number: '27229' name: 'A Tale of Two Circuits: Rostrocaudal spinal cord patterning during the swim-to-limb transition of Xenopus metamorphosis' publication: Xenopus publication_identifier: eissn: - 1940-6029 publication_status: published publisher: Springer quality_controlled: '1' researchdata_availability: no scopus_import: '1' series_title: MIMB status: public supplementarymaterial: no title: Fluorescent in situ mRNA hybridization (FISH) using Hybridization Chain Reaction (HCR) in Xenopus cryosections tmp: image: /images/cc_by_nc_nd.png legal_code_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode name: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) short: CC BY-NC-ND (4.0) type: book_chapter user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 3049 year: '2026' ... --- OA_place: publisher OA_type: gold _id: '22920' abstract: - lang: eng text: "Two-player games on graphs are a classical framework for analyzing strategic decision making. In turn-based games, two players move a token along the edges of the graph, and the right to move the token is determined by the current vertex. In traditional bidding games - referred to as pure bidding games - the right to move the token is determined at each step through bidding; here we consider Richman bidding, where the winning player of a bid pays the losing player. The winner is decided based on a temporal or quantitative specification evaluated over the resulting infinite play.\r\nIn this work, we combine turn-based games and pure bidding games into generalized bidding games, with player-1 vertices, player-2 vertices, and bidding vertices. This natural and simple generalization of bidding games has far-reaching consequences. First, we show that, as a model, generalized bidding games are more expressive than pure bidding games, and we provide several applications. Second, and most importantly, we show that generalized Richman bidding games are structurally equivalent to simple stochastic games, a well-studied model: they are linearly interreducible to each other. As was previously known, the special case of pure Richman bidding games corresponds to random-turn games. In other words, generalized bidding games extend pure bidding games in the same way that simple stochastic games extend random-turn games. We use this connection to solve generalized Richman bidding games for temporal (parity) and quantitative (mean-payoff and discounted-sum) specifications. From a computational perspective, we establish that generalized bidding games with parity and mean-payoff specifications retain the best known upper bounds for turn-based games and pure bidding games, namely NP∩coNP.\r\nFinally, we study a repair problem that asks whether bidding vertices can be assigned \"owners\" so as to bring the threshold budget required to win the game below a given target. This problem has direct applications in compositional policy synthesis for multi-objective settings, and we show it to be NP-complete." acknowledgement: "The research was partially supported by Austrian Science Fund (FWF) 10.55776/COE12,\r\nERC CoG 863818 (ForM-SMArt), FWF-2022-SFB F8502 (SPyCoDe), ERC-2020-AdG 101020093\r\n(VAMOS), and the RYC2024-049116-I grant funded by MICIU/AEI/10.13039/501100011033 and\r\nESF+.\r\n" alternative_title: - LIPIcs article_number: 13:1-13:20 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: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000-0002-2985-7724 - first_name: Ehsan full_name: Kafshdar Goharshadi, Ehsan id: 103b4fa0-896a-11ed-bdf8-87b697bef40d last_name: Kafshdar Goharshadi orcid: 0000-0002-8595-0587 - first_name: Pavol full_name: Kebis, Pavol id: 2e0132b3-4e98-11ef-b275-cf7281c2802a last_name: Kebis - first_name: Kaushik full_name: Mallik, Kaushik id: 0834ff3c-6d72-11ec-94e0-b5b0a4fb8598 last_name: Mallik orcid: 0000-0001-9864-7475 citation: ama: 'Asadi A, Henzinger TA, Goharshady E, Kebis P, Mallik K. Generalized bidding games: Where bidding and stochastic games meet. In: 37th International Conference on Concurrency Theory. Vol 391. Schloss Dagstuhl - Leibniz-Zentrum für Informatik; 2026. doi:10.4230/LIPIcs.CONCUR.2026.13' apa: 'Asadi, A., Henzinger, T. A., Goharshady, E., Kebis, P., & Mallik, K. (2026). Generalized bidding games: Where bidding and stochastic games meet. In 37th International Conference on Concurrency Theory (Vol. 391). Liverpool, United Kingdom: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.CONCUR.2026.13' chicago: 'Asadi, Ali, Thomas A Henzinger, Ehsan Goharshady, Pavol Kebis, and Kaushik Mallik. “Generalized Bidding Games: Where Bidding and Stochastic Games Meet.” In 37th International Conference on Concurrency Theory, Vol. 391. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2026. https://doi.org/10.4230/LIPIcs.CONCUR.2026.13.' ieee: 'A. Asadi, T. A. Henzinger, E. Goharshady, P. Kebis, and K. Mallik, “Generalized bidding games: Where bidding and stochastic games meet,” in 37th International Conference on Concurrency Theory, Liverpool, United Kingdom, 2026, vol. 391.' ista: 'Asadi A, Henzinger TA, Goharshady E, Kebis P, Mallik K. 2026. Generalized bidding games: Where bidding and stochastic games meet. 37th International Conference on Concurrency Theory. CONCUR: Conference on Concurrency Theory, LIPIcs, vol. 391, 13:1-13:20.' mla: 'Asadi, Ali, et al. “Generalized Bidding Games: Where Bidding and Stochastic Games Meet.” 37th International Conference on Concurrency Theory, vol. 391, 13:1-13:20, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2026, doi:10.4230/LIPIcs.CONCUR.2026.13.' short: A. Asadi, T.A. Henzinger, E. Goharshady, P. Kebis, K. Mallik, in:, 37th International Conference on Concurrency Theory, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2026. conference: end_date: 2026-09-04 location: Liverpool, United Kingdom name: 'CONCUR: Conference on Concurrency Theory' start_date: 2026-09-01 corr_author: '1' das_tickbox: '0' date_created: 2026-09-13T22:01:53Z date_published: 2026-08-24T00:00:00Z date_updated: 2026-09-17T09:44:41Z day: '24' ddc: - '000' department: - _id: GradSch - _id: KrCh - _id: ToHe doi: 10.4230/LIPIcs.CONCUR.2026.13 ec_funded: 1 external_id: arxiv: - '2606.29420' file: - access_level: open_access checksum: de9af748d78fa42c173f68a71cbbd8d9 content_type: application/pdf creator: dernst date_created: 2026-09-17T09:43:28Z date_updated: 2026-09-17T09:43:28Z file_id: '22946' file_name: 2026_LIPIcsCONCUR_Asadi.pdf file_size: 1175682 relation: main_file success: 1 file_date_updated: 2026-09-17T09:43:28Z fulldoi: https://doi.org/10.4230/LIPIcs.CONCUR.2026.13 has_accepted_license: '1' intvolume: ' 391' keyword: - Bidding Games - Stochastic Games language: - iso: eng month: '08' oa: 1 oa_version: Published Version project: - _id: 4029cfc7-b034-11f1-9e55-88ab2ff3b6ee grant_number: COE12 name: Bilateral Artificial Intelligence (Chatterjee) - _id: 0599E47C-7A3F-11EA-A408-12923DDC885E call_identifier: H2020 grant_number: '863818' name: 'Formal Methods for Stochastic Models: Algorithms and Applications' - _id: 34a1b658-11ca-11ed-8bc3-c75229f0241e grant_number: F8502 name: Interface Theory for Security and Privacy - _id: 62781420-2b32-11ec-9570-8d9b63373d4d call_identifier: H2020 grant_number: '101020093' name: Vigilant Algorithmic Monitoring of Software publication: 37th International Conference on Concurrency Theory publication_identifier: eissn: - 1868-8969 isbn: - '9783959774475' publication_status: published publisher: Schloss Dagstuhl - Leibniz-Zentrum für Informatik quality_controlled: '1' researchdata_availability: no scopus_import: '1' status: public supplementarymaterial: yes title: 'Generalized bidding games: Where bidding and stochastic games meet' 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: 391 year: '2026' ... --- OA_place: publisher OA_type: gold _id: '22919' abstract: - lang: eng text: 'Reachability is the most fundamental logical objective, yet it is notoriously difficult to learn in reinforcement learning settings: even for Markov decision processes, PAC learning of reachability is impossible without additional assumptions. This difficulty also holds in turn-based stochastic games (TBSGs), where two adversarial players interact on a finite state space. In this work, we consider turn-based stochastic games with reachability objectives. For such settings, adversarial learning, in which players are adversarial even in the learning phase, is impossible. Therefore, the goal is to consider learning, in which both players learn the unknown model together. In this spirit, previous literature on PAC learning in TBSGs considers (a) public information shared by both players; and (b) centralized learning, which means that players share the same learning algorithm. In this work, our contribution is two-fold. First, we relax these strong assumptions and ensure learning: (i) with private information not shared with the other player; and (ii) decentralized learning where the players do not share the same learning algorithm. To the best of our knowledge, this work is the first positive result for decentralized and private information learning of TBSGs with reachability objectives. Second, we introduce a game-theoretic generalization of the Expected Conditional Distance (ECD) parameter, which measures the expected length of reaching the target set. We establish a polynomial-sample complexity bound with respect to the number of states, actions, ECD parameter, and inverses of error tolerance and failure probability.' acknowledgement: "The research was partially supported by Austrian Science Fund (FWF) 10.55776/COE12,\r\nERC CoG 863818 (ForM-SMArt), FWF-2022-SFB F8502 (SPyCoDe), and ERC-2020-AdG 101020093\r\n(VAMOS) grants." alternative_title: - LIPIcs article_number: 12:1-12:23 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: Krishnendu full_name: Chatterjee, Krishnendu id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87 last_name: Chatterjee orcid: 0000-0002-4561-241X - first_name: Pavol full_name: Kebis, Pavol id: 2e0132b3-4e98-11ef-b275-cf7281c2802a last_name: Kebis citation: ama: 'Asadi A, Chatterjee K, Kebis P. PAC learning in turn-based stochastic games with reachability objectives: A decentralized private approach via expected conditional distance. In: 37th International Conference on Concurrency Theory. Vol 391. Schloss Dagstuhl - Leibniz-Zentrum für Informatik; 2026. doi:10.4230/LIPIcs.CONCUR.2026.12' apa: 'Asadi, A., Chatterjee, K., & Kebis, P. (2026). PAC learning in turn-based stochastic games with reachability objectives: A decentralized private approach via expected conditional distance. In 37th International Conference on Concurrency Theory (Vol. 391). Liverpool, United Kingdom: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.CONCUR.2026.12' chicago: 'Asadi, Ali, Krishnendu Chatterjee, and Pavol Kebis. “PAC Learning in Turn-Based Stochastic Games with Reachability Objectives: A Decentralized Private Approach via Expected Conditional Distance.” In 37th International Conference on Concurrency Theory, Vol. 391. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2026. https://doi.org/10.4230/LIPIcs.CONCUR.2026.12.' ieee: 'A. Asadi, K. Chatterjee, and P. Kebis, “PAC learning in turn-based stochastic games with reachability objectives: A decentralized private approach via expected conditional distance,” in 37th International Conference on Concurrency Theory, Liverpool, United Kingdom, 2026, vol. 391.' ista: 'Asadi A, Chatterjee K, Kebis P. 2026. PAC learning in turn-based stochastic games with reachability objectives: A decentralized private approach via expected conditional distance. 37th International Conference on Concurrency Theory. CONCUR: Conference on Concurrency Theory, LIPIcs, vol. 391, 12:1-12:23.' mla: 'Asadi, Ali, et al. “PAC Learning in Turn-Based Stochastic Games with Reachability Objectives: A Decentralized Private Approach via Expected Conditional Distance.” 37th International Conference on Concurrency Theory, vol. 391, 12:1-12:23, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2026, doi:10.4230/LIPIcs.CONCUR.2026.12.' short: A. Asadi, K. Chatterjee, P. Kebis, in:, 37th International Conference on Concurrency Theory, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2026. conference: end_date: 2026-09-04 location: Liverpool, United Kingdom name: 'CONCUR: Conference on Concurrency Theory' start_date: 2026-09-01 corr_author: '1' das_tickbox: '0' date_created: 2026-09-13T22:01:53Z date_published: 2026-08-24T00:00:00Z date_updated: 2026-09-17T09:51:25Z day: '24' ddc: - '000' department: - _id: GradSch - _id: KrCh - _id: ToHe doi: 10.4230/LIPIcs.CONCUR.2026.12 ec_funded: 1 external_id: arxiv: - '2607.14877' file: - access_level: open_access checksum: 2e6c55b65d9d7ce436a6f59e81d7ba17 content_type: application/pdf creator: dernst date_created: 2026-09-17T09:50:00Z date_updated: 2026-09-17T09:50:00Z file_id: '22947' file_name: 2026_LIPIcsCONCUR_Asadi2.pdf file_size: 959234 relation: main_file success: 1 file_date_updated: 2026-09-17T09:50:00Z fulldoi: https://doi.org/10.4230/LIPIcs.CONCUR.2026.12 has_accepted_license: '1' intvolume: ' 391' keyword: - formal methods - games and logic - logical aspects of AI - model checking language: - iso: eng month: '08' oa: 1 oa_version: Published Version project: - _id: 4029cfc7-b034-11f1-9e55-88ab2ff3b6ee grant_number: COE12 name: Bilateral Artificial Intelligence (Chatterjee) - _id: 0599E47C-7A3F-11EA-A408-12923DDC885E call_identifier: H2020 grant_number: '863818' name: 'Formal Methods for Stochastic Models: Algorithms and Applications' - _id: 34a1b658-11ca-11ed-8bc3-c75229f0241e grant_number: F8502 name: Interface Theory for Security and Privacy - _id: 62781420-2b32-11ec-9570-8d9b63373d4d call_identifier: H2020 grant_number: '101020093' name: Vigilant Algorithmic Monitoring of Software publication: 37th International Conference on Concurrency Theory publication_identifier: eissn: - 1868-8969 isbn: - '9783959774475' publication_status: published publisher: Schloss Dagstuhl - Leibniz-Zentrum für Informatik quality_controlled: '1' researchdata_availability: no scopus_import: '1' status: public supplementarymaterial: yes title: 'PAC learning in turn-based stochastic games with reachability objectives: A decentralized private approach via expected conditional distance' 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: 391 year: '2026' ... --- DOAJ_listed: '1' OA_place: publisher OA_type: gold PlanS_conform: '1' _id: '22408' abstract: - lang: eng text: Solitons—localized wave packets that travel without spreading—play a central role in understanding transport and properties of nonlinear systems. In quantum many-body systems, however, such robust excitations are typically destroyed by thermalization. Here, we theoretically demonstrate the existence of solitonic excitations in high-energy states of Rydberg atom chains in the regime of strong nearest-neighbor Rydberg blockade. These localized wave packets propagate directionally atop a special class of reviving initial states related to quantum many-body scars and are capable of carrying energy. Exhibiting long coherence times, these states constitute a form of non-ergodic quantum dynamics and can be efficiently implemented on Rydberg atom simulators. In this work, in addition to a phenomenological description of solitons, we identify their counterpart in a classical nonlinear dynamical system, demonstrate their potential use in quantum information transfer, and conjecture their relevance for anomalous energy transport reported in numerical studies of Rydberg atom arrays. acknowledgement: We acknowledge useful discussions with J.-S. Caux, E. Demler, J. Dubail, F. Essler, J. Feldmeier, S. Garratt, W. W. Ho, M. Lukin, Z. Papic, S. Rotter, F. Surace, and R. Vasseur. J.-Y.D. acknowledges funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 101034413. M. L. acknowledges support by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy—EXC-2111—390814868. We acknowledge support by the Erwin Schrödinger International Institute for Mathematics and Physics (ESI). This research was funded in part by the Austrian Science Fund (FWF) https://doi.org/10.55776/COE1 and the European Union—NextGenerationEU. This research was supported in part by grant NSF PHY2309135 to the Kavli Institute for Theoretical Physics (KITP). article_number: '8783' article_processing_charge: Yes article_type: original author: - first_name: Aron full_name: Kerschbaumer, Aron id: ade85a9c-3200-11ee-973b-91c1eb240410 last_name: Kerschbaumer orcid: 0009-0002-2370-8661 - first_name: Jean-Yves Marc full_name: Desaules, Jean-Yves Marc id: 6c292945-a610-11ed-9eec-c3be1ad62a80 last_name: Desaules orcid: 0000-0002-3749-6375 - first_name: Marko full_name: Ljubotina, Marko id: F75EE9BE-5C90-11EA-905D-16643DDC885E last_name: Ljubotina orcid: 0000-0003-0038-7068 - first_name: Maksym full_name: Serbyn, Maksym id: 47809E7E-F248-11E8-B48F-1D18A9856A87 last_name: Serbyn orcid: 0000-0002-2399-5827 citation: ama: Kerschbaumer A, Desaules J-YM, Ljubotina M, Serbyn M. Quasi-solitons in Rydberg atom chains. Nature Communications. 2026;17. doi:10.1038/s41467-026-75598-1 apa: Kerschbaumer, A., Desaules, J.-Y. M., Ljubotina, M., & Serbyn, M. (2026). Quasi-solitons in Rydberg atom chains. Nature Communications. Springer Nature. https://doi.org/10.1038/s41467-026-75598-1 chicago: Kerschbaumer, Aron, Jean-Yves Marc Desaules, Marko Ljubotina, and Maksym Serbyn. “Quasi-Solitons in Rydberg Atom Chains.” Nature Communications. Springer Nature, 2026. https://doi.org/10.1038/s41467-026-75598-1. ieee: A. Kerschbaumer, J.-Y. M. Desaules, M. Ljubotina, and M. Serbyn, “Quasi-solitons in Rydberg atom chains,” Nature Communications, vol. 17. Springer Nature, 2026. ista: Kerschbaumer A, Desaules J-YM, Ljubotina M, Serbyn M. 2026. Quasi-solitons in Rydberg atom chains. Nature Communications. 17, 8783. mla: Kerschbaumer, Aron, et al. “Quasi-Solitons in Rydberg Atom Chains.” Nature Communications, vol. 17, 8783, Springer Nature, 2026, doi:10.1038/s41467-026-75598-1. short: A. Kerschbaumer, J.-Y.M. Desaules, M. Ljubotina, M. Serbyn, Nature Communications 17 (2026). corr_author: '1' das_tickbox: '1' dataavailabilitystatement: The raw data used to generate the figures are available at ref54.The TEBD algorithm used in this work was implemented using the ITensor library48,49 and the integration of the classical differential equations was performed via SciPy’s Runge-Kutta RK45 integrator52,53. The code used in this study to produce the plots from the shared data is available at ref.54. date_created: 2026-07-27T07:26:27Z date_published: 2026-08-21T00:00:00Z date_updated: 2026-09-17T10:54:09Z day: '21' ddc: - '530' department: - _id: MaSe - _id: GradSch doi: 10.1038/s41467-026-75598-1 ec_funded: 1 external_id: pmid: - '42469244' file: - access_level: open_access checksum: 2e12ade81e19b7eea099a2196217edff content_type: application/pdf creator: dernst date_created: 2026-09-09T07:04:48Z date_updated: 2026-09-09T07:04:48Z file_id: '22863' file_name: 2026_NatureComm_Kerschbaumer.pdf file_size: 1337815 relation: main_file success: 1 file_date_updated: 2026-09-09T07:04:48Z fulldoi: https://doi.org/10.1038/s41467-026-75598-1 has_accepted_license: '1' intvolume: ' 17' language: - iso: eng month: '08' oa: 1 oa_version: Published Version pmid: 1 project: - _id: fc2ed2f7-9c52-11eb-aca3-c01059dda49c call_identifier: H2020 grant_number: '101034413' name: 'IST-BRIDGE: International postdoctoral program' - _id: 92c64506-16d5-11f0-9cad-87ce313ee832 grant_number: COE01 name: Quantum Science Austria (Serbyn) publication: Nature Communications publication_identifier: eissn: - 2041-1723 publication_status: published publisher: Springer Nature quality_controlled: '1' related_material: record: - id: '21960' relation: research_data status: public researchdata_availability: yes scopus_import: '1' status: public supplementarymaterial: yes title: Quasi-solitons in Rydberg atom chains 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: 17 year: '2026' ... --- OA_place: repository _id: '21960' abstract: - lang: eng text: "Solitons - localized wave packets that travel without spreading - play a central role in understanding transport and properties of nonlinear systems. In quantum many-body systems, however, such robust excitations are typically destroyed by thermalization. Here, we theoretically demonstrate the existence of solitonic excitations in high-energy states of Rydberg atom chains in the regime of strong nearest-neighbor Rydberg blockade. \r\nThese localized wave packets propagate directionally atop a special class of reviving initial states related to quantum many-body scars and are capable of carrying energy. Exhibiting long coherence times, these states constitute a form of non-ergodic quantum dynamics and can be efficiently implemented on Rydberg atom simulators. In this work, in addition to a phenomenological description of solitons, we identify their counterpart in a classical nonlinear dynamical system, demonstrate their potential use in quantum information transfer, and conjecture their relevance for anomalous energy transport reported in numerical studies of Rydberg atom arrays." article_processing_charge: No author: - first_name: Aron full_name: Kerschbaumer, Aron id: ade85a9c-3200-11ee-973b-91c1eb240410 last_name: Kerschbaumer orcid: 0009-0002-2370-8661 citation: ama: 'Kerschbaumer A. Research Data: “Quasi-solitons in Rydberg atom chains.” 2026. doi:10.15479/AT-ISTA-21960' apa: 'Kerschbaumer, A. (2026). Research Data: “Quasi-solitons in Rydberg atom chains.” Institute of Science and Technology Austria. https://doi.org/10.15479/AT-ISTA-21960' chicago: 'Kerschbaumer, Aron. “Research Data: ‘Quasi-Solitons in Rydberg Atom Chains.’” Institute of Science and Technology Austria, 2026. https://doi.org/10.15479/AT-ISTA-21960.' ieee: 'A. Kerschbaumer, “Research Data: ‘Quasi-solitons in Rydberg atom chains.’” Institute of Science and Technology Austria, 2026.' ista: 'Kerschbaumer A. 2026. Research Data: ‘Quasi-solitons in Rydberg atom chains’, Institute of Science and Technology Austria, 10.15479/AT-ISTA-21960.' mla: 'Kerschbaumer, Aron. Research Data: “Quasi-Solitons in Rydberg Atom Chains.” Institute of Science and Technology Austria, 2026, doi:10.15479/AT-ISTA-21960.' short: A. Kerschbaumer, (2026). contributor: - contributor_type: contact_person first_name: Aron id: ade85a9c-3200-11ee-973b-91c1eb240410 last_name: Kerschbaumer orcid: 0009-0002-2370-8661 - contributor_type: supervisor first_name: Maksym id: 47809E7E-F248-11E8-B48F-1D18A9856A87 last_name: Serbyn orcid: 0000-0002-2399-5827 - contributor_type: researcher first_name: Jean-Yves Marc id: 6c292945-a610-11ed-9eec-c3be1ad62a80 last_name: Desaules orcid: 0000-0002-3749-6375 - contributor_type: researcher first_name: Marko last_name: Ljubotina corr_author: '1' date_created: 2026-06-09T07:17:50Z date_published: 2026-06-16T00:00:00Z date_updated: 2026-09-17T10:54:08Z day: '16' department: - _id: GradSch - _id: MaSe doi: 10.15479/AT-ISTA-21960 ec_funded: 1 file: - access_level: open_access checksum: 133269a105e996c6c44fdd56128259c7 content_type: text/plain creator: akerschb date_created: 2026-06-15T22:01:57Z date_updated: 2026-06-15T22:01:57Z file_id: '22010' file_name: README.txt file_size: 1940 relation: main_file success: 1 - access_level: open_access checksum: 759f9649c3919f4c4ad37a1d104ea32a content_type: application/zip creator: akerschb date_created: 2026-06-15T22:02:07Z date_updated: 2026-06-15T22:02:07Z file_id: '22011' file_name: Soliton_Data.zip file_size: 13259747 relation: main_file success: 1 file_date_updated: 2026-06-15T22:02:07Z fulldoi: https://doi.org/10.15479/AT-ISTA-21960 has_accepted_license: '1' license: https://creativecommons.org/licenses/by-nc/4.0/ month: '06' 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' publisher: Institute of Science and Technology Austria related_material: record: - id: '22408' relation: used_in_publication status: public status: public title: 'Research Data: "Quasi-solitons in Rydberg atom chains"' 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: research_data user_id: 68b8ca59-c5b3-11ee-8790-cd641c68093d year: '2026' ... --- OA_place: publisher _id: '22808' abstract: - lang: eng text: "As automated decision-makers have become ubiquitous in many domains of life,\r\ntheir decisions have become increasingly consequential. Recent years have shown\r\nthat such systems can exhibit discriminatory behaviour against individuals and\r\nsocial groups alike, thereby amplifying existing biases and entrenching\r\nsocio-economic disparities over time. Algorithmic fairness addresses this\r\nproblem by developing methods to quantify and mitigate unfair behaviour.\r\nHowever, much of the existing literature studies fairness in a static\r\npre-deployment setting and, therefore, neglects that automated decision-makers are\r\noften deployed in dynamic environments, where their behaviour and the\r\npopulations they affect may change over time.\r\n\r\nThis thesis addresses this gap through the lens of runtime verification.\r\nInstead of treating fairness as a property of a classifier together with a fixed\r\ninput distribution, it reframes fairness as a property of the interaction trace\r\nbetween the decision-maker and its deployment environment. To evaluate such\r\nsequential fairness properties, the thesis develops runtime monitors that\r\nobserve the evolving interaction between the system and the environment and\r\nissue verdicts after each new observation. Because, these monitors are designed to detect\r\nunfair behaviour during deployment, they complement fair training,\r\nauditing, verification, and enforcement by providing an additional layer of mathematically rigorous fairness assurance.\r\n\r\nIn summary, the thesis develops quantitative, trace-based analogues of\r\nclassical group and individual fairness measures and constructs monitors for\r\nthem. This includes monitors for long-run group fairness over Markovian traces,\r\nfor the time-varying welfare of a changing population in a dynamical system, and\r\nfor the individual fairness of an arbitrary system generating a trace of inputs\r\nand outputs. To achieve this, the monitors combine ideas from runtime\r\nverification, sequential statistics, and nearest-neighbour search. In the\r\ngroup-fairness settings, monitoring is primarily a sequential statistical\r\nestimation problem: the monitor must construct statistically sound interval\r\nestimates of fairness values from dependent and partially observed interactions.\r\nIn the individual-fairness setting, the main challenge is computational\r\nefficiency: the monitor must detect individual fairness violations by efficiently comparing the\r\ncurrent decision with all previously observed decisions.\r\n" acknowledgement: "This work was supported in part by the ERC-2020-AdG 101020093 (VAMOS).\r\n" alternative_title: - ISTA Thesis article_processing_charge: No author: - first_name: Konstantin full_name: Kueffner, Konstantin id: 8121a2d0-dc85-11ea-9058-af578f3b4515 last_name: Kueffner orcid: 0000-0001-8974-2542 citation: ama: Kueffner K. Monitoring algorithmic fairness in sequential decision making. 2026. doi:10.15479/AT-ISTA-22808 apa: Kueffner, K. (2026). Monitoring algorithmic fairness in sequential decision making. Institute of Science and Technology Austria. https://doi.org/10.15479/AT-ISTA-22808 chicago: Kueffner, Konstantin. “Monitoring Algorithmic Fairness in Sequential Decision Making.” Institute of Science and Technology Austria, 2026. https://doi.org/10.15479/AT-ISTA-22808. ieee: K. Kueffner, “Monitoring algorithmic fairness in sequential decision making,” Institute of Science and Technology Austria, 2026. ista: Kueffner K. 2026. Monitoring algorithmic fairness in sequential decision making. Institute of Science and Technology Austria. mla: Kueffner, Konstantin. Monitoring Algorithmic Fairness in Sequential Decision Making. Institute of Science and Technology Austria, 2026, doi:10.15479/AT-ISTA-22808. short: K. Kueffner, Monitoring Algorithmic Fairness in Sequential Decision Making, Institute of Science and Technology Austria, 2026. corr_author: '1' date_created: 2026-09-05T15:59:19Z date_published: 2026-09-07T00:00:00Z date_updated: 2026-09-18T07:41:29Z day: '07' ddc: - '000' degree_awarded: PhD department: - _id: GradSch - _id: ToHe doi: 10.15479/AT-ISTA-22808 doi_confirm: '1' ec_funded: 1 file: - access_level: closed checksum: 716ce44a6ed9a727f231bdebdeecc741 content_type: application/zip creator: kkueffne date_created: 2026-09-11T07:32:13Z date_updated: 2026-09-11T07:32:13Z file_id: '22903' file_name: Thesis_Konstantin_Kueffner-3.zip file_size: 26356903 relation: source_file - access_level: open_access checksum: 77082e90b8330fb46f585843840c5d5c content_type: application/pdf creator: kkueffne date_created: 2026-09-11T07:32:17Z date_updated: 2026-09-11T07:32:17Z file_id: '22904' file_name: Thesis_Konstantin_Kueffner-2.pdf file_size: 10051715 relation: main_file file_date_updated: 2026-09-11T07:32:17Z fulldoi: https://doi.org/10.15479/AT-ISTA-22808 has_accepted_license: '1' language: - iso: eng month: '09' oa: 1 oa_version: Published Version page: '183' project: - _id: 62781420-2b32-11ec-9570-8d9b63373d4d call_identifier: H2020 grant_number: '101020093' name: Vigilant Algorithmic Monitoring of Software publication_identifier: isbn: - 978-3-99078-089-3 issn: - 2663-337X publication_status: published publisher: Institute of Science and Technology Austria related_material: record: - id: '13310' relation: part_of_dissertation status: public - id: '14454' relation: part_of_dissertation status: public - id: '20292' relation: part_of_dissertation status: public - id: '21090' relation: part_of_dissertation status: public - id: '13228' relation: part_of_dissertation status: public status: public supervisor: - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000-0002-2985-7724 title: Monitoring algorithmic fairness in sequential decision making 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: 8b945eb4-e2f2-11eb-945a-df72226e66a9 year: '2026' ... --- OA_place: publisher _id: '22873' acknowledged_ssus: - _id: ScienComp - _id: CampIT acknowledgement: I acknowledge funding by the Austrian Science Fund (FWF) [10.55776/PAT8537123]. alternative_title: - ISTA Thesis article_processing_charge: No author: - first_name: Andreas full_name: Ehrmann, Andreas id: eaa689ed-f6e0-11ea-865d-bd98cbcf83c2 last_name: Ehrmann orcid: 0000-0002-0997-5678 citation: ama: 'Ehrmann A. Biological functionality without biochemistry: Designing nanomachines for target behavior. 2026. doi:10.15479/AT-ISTA-22873' apa: 'Ehrmann, A. (2026). Biological functionality without biochemistry: Designing nanomachines for target behavior. Institute of Science and Technology Austria. https://doi.org/10.15479/AT-ISTA-22873' chicago: 'Ehrmann, Andreas. “Biological Functionality without Biochemistry: Designing Nanomachines for Target Behavior.” Institute of Science and Technology Austria, 2026. https://doi.org/10.15479/AT-ISTA-22873.' ieee: 'A. Ehrmann, “Biological functionality without biochemistry: Designing nanomachines for target behavior,” Institute of Science and Technology Austria, 2026.' ista: 'Ehrmann A. 2026. Biological functionality without biochemistry: Designing nanomachines for target behavior. Institute of Science and Technology Austria.' mla: 'Ehrmann, Andreas. Biological Functionality without Biochemistry: Designing Nanomachines for Target Behavior. Institute of Science and Technology Austria, 2026, doi:10.15479/AT-ISTA-22873.' short: 'A. Ehrmann, Biological Functionality without Biochemistry: Designing Nanomachines for Target Behavior, Institute of Science and Technology Austria, 2026.' corr_author: '1' das_tickbox: '0' date_created: 2026-09-09T12:18:24Z date_published: 2026-09-04T00:00:00Z date_updated: 2026-09-18T11:28:29Z day: '04' ddc: - '530' - '600' - '621' - '004' - '005' degree_awarded: PhD department: - _id: GradSch - _id: CaGo - _id: EdHa doi: 10.15479/AT-ISTA-22873 doi_confirm: '1' file: - access_level: closed checksum: a5e3d79e0e5f3f4fb3c414e48116dc9e content_type: application/pdf creator: aehrmann date_created: 2026-09-11T07:23:57Z date_updated: 2026-09-17T08:59:39Z embargo: 2027-01-15 embargo_to: open_access file_id: '22901' file_name: 2026_Ehrmann_Andreas_Thesis.pdf file_size: 14782662 relation: main_file - access_level: closed checksum: 0235b9c52fee0c97f402f1c3d4efc1eb content_type: application/zip creator: aehrmann date_created: 2026-09-11T07:24:14Z date_updated: 2026-09-11T07:24:14Z description: All LaTeX files to compile my PhD Thesis. file_id: '22902' file_name: thesis_latex_files.zip file_size: 155228 relation: source_file file_date_updated: 2026-09-17T08:59:39Z fulldoi: https://doi.org/10.15479/AT-ISTA-22873 has_accepted_license: '1' keyword: - PhD Thesis - functional nanomachines - biological functionality - nanotechnology - energy delivery - target behavior - dynamics - design principles - optimization - differentiable statistical physics - machine learning language: - iso: eng license: https://creativecommons.org/licenses/by-nc-sa/4.0/ month: '09' oa_version: Published Version page: '168' project: - _id: 90a98bb5-16d5-11f0-9cad-9675f3f8015d grant_number: PAT 8537123 name: Functional bio-inspired nanomachines from sticky colloids publication_identifier: isbn: - 978-3-99078-092-3 issn: - 2663-337X publication_status: published publisher: Institute of Science and Technology Austria related_material: record: - id: '22893' relation: part_of_dissertation status: public - id: '22892' relation: part_of_dissertation status: public researchdata_availability: upon request status: public supervisor: - first_name: Carl Peter full_name: Goodrich, Carl Peter id: EB352CD2-F68A-11E9-89C5-A432E6697425 last_name: Goodrich orcid: 0000-0002-1307-5074 - first_name: Edouard B full_name: Hannezo, Edouard B id: 3A9DB764-F248-11E8-B48F-1D18A9856A87 last_name: Hannezo orcid: 0000-0001-6005-1561 supplementarymaterial: not applicable title: 'Biological functionality without biochemistry: Designing nanomachines for target behavior' tmp: image: /images/cc_by_nc_sa.png legal_code_url: https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode name: Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) short: CC BY-NC-SA (4.0) type: dissertation user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9 year: '2026' ... --- OA_place: publisher _id: '22857' abstract: - lang: eng text: "Artificial intelligence and machine learning have undergone an unprecedented evolution in the past decade, motivating a research effort toward a theory able to capture the qualitative behavior of large-scale neural systems. A central puzzle has been the clear benefit of scaling architecture size and overfitting the training set in supervised learning tasks. This evidence, in apparent contradiction with classical statistical learning theory, pushed researchers to develop a new theory capturing the interplay between the algorithmic and architectural bias of training and the specific target function, differently from previous methods rooted in uniform stability.\r\nThis approach has enabled a grounded understanding of novel learning regimes, typically through formal limits where the number of training samples $n$, data dimensions $d$, and model parameters $p$ grow to infinity at different rates. \\\\\r\nIn this thesis, we follow this approach, focusing on the trustworthiness of high-dimensional models: properties that are difficult to control during training or deployment and often emerge under unpredictable or adversarial conditions. In such settings, it is crucial to formally ensure a priori the reliability of machine learning systems.\r\nFirst, we study data memorization, both as label fitting and as the storage of private information about training samples in trained parameters. We prove that $p = \\Omega(n)$ parameters are sufficient for a deep neural network to memorize a generic set of labels, and for a model to memorize spurious features across training data. We then give evidence that $p = \\Omega(dn)$ parameters are instead necessary for an adversary to reconstruct the full training set from the trained parameters.\r\nSecond, we study robustness, both to adversarial perturbations and to distribution shift. We first prove that $p = \\Omega(dn)$ parameters can be sufficient for a class of neural networks to overfit the training data while guaranteeing robustness to adversarial perturbations. Then, we focus on spurious correlations learning in high-dimensional regression, studying the effect of the ridge regularization parameter in the proportional regime $n = \\Theta(d)$, and connecting it via an equivalence argument to the role of over-parameterization $p = \\Omega(n)$ in neural networks. We also investigate the architectural bias of attention-based networks, showing that they are sensitive to the replacement of individual words in an embedded sentence, allowing them to generalize on sentences where the contextual meaning depends on one or few words.\r\nFinally, we study differentially private optimization in high-dimensional regimes. We prove that standard private gradient methods do not suffer in the over-parameterized regime $p = \\Omega(n)$, challenging the current wisdom based on stability-derived generalization bounds. We then consider linear regression in the proportional regime $n = \\Theta(d)$, showing that standard private gradient descent can achieve optimal rates under appropriate hyper-parameter scaling, such as sufficiently small gradient clipping constants, whose role is still debated in practice." acknowledged_ssus: - _id: ScienComp acknowledgement: "This project was partially supported by the 2019 Lopez-Loreta prize,\r\nthe European Union (ERC, INF2\r\n, project number 101161364), the Austrian Science Fund\r\n(FWF) 10.55776/COE12, and a Google PhD fellowship in machine intelligence. Furthermore,\r\nthe candidate acknowledges the support from the Scientific Service Units of the Institute of\r\nScience and Technology Austria through resources provided by Scientific Computing." alternative_title: - ISTA Thesis article_processing_charge: No author: - first_name: Simone full_name: Bombari, Simone id: ca726dda-de17-11ea-bc14-f9da834f63aa last_name: Bombari citation: ama: Bombari S. Trustworthy machine learning in high dimensions. 2026. doi:10.15479/AT-ISTA-22857 apa: Bombari, S. (2026). Trustworthy machine learning in high dimensions. Institute of Science and Technology Austria. https://doi.org/10.15479/AT-ISTA-22857 chicago: Bombari, Simone. “Trustworthy Machine Learning in High Dimensions.” Institute of Science and Technology Austria, 2026. https://doi.org/10.15479/AT-ISTA-22857. ieee: S. Bombari, “Trustworthy machine learning in high dimensions,” Institute of Science and Technology Austria, 2026. ista: Bombari S. 2026. Trustworthy machine learning in high dimensions. Institute of Science and Technology Austria. mla: Bombari, Simone. Trustworthy Machine Learning in High Dimensions. Institute of Science and Technology Austria, 2026, doi:10.15479/AT-ISTA-22857. short: S. Bombari, Trustworthy Machine Learning in High Dimensions, Institute of Science and Technology Austria, 2026. corr_author: '1' das_tickbox: '0' date_created: 2026-09-08T13:40:08Z date_published: 2026-09-08T00:00:00Z date_updated: 2026-09-21T13:07:01Z day: '08' ddc: - '519' degree_awarded: PhD department: - _id: GradSch - _id: MaMo doi: 10.15479/AT-ISTA-22857 doi_confirm: '1' file: - access_level: closed checksum: 8eab99d6dc6e4476826bdfc7c00fdebb content_type: application/zip creator: sbombari date_created: 2026-09-08T13:28:38Z date_updated: 2026-09-08T13:28:38Z file_id: '22859' file_name: Thesis copy.zip file_size: 99154325 relation: source_file - access_level: open_access checksum: 007033bafe4622ff4c2e758301354df1 content_type: application/pdf creator: sbombari date_created: 2026-09-10T10:03:48Z date_updated: 2026-09-10T10:03:48Z file_id: '22898' file_name: 2026_Bombari_Simone_Thesis.pdf file_size: 12856211 relation: main_file success: 1 file_date_updated: 2026-09-10T10:03:48Z fulldoi: https://doi.org/10.15479/AT-ISTA-22857 has_accepted_license: '1' keyword: - machine learning - high-dimensional statistics - deep learning theory - privacy - memorization - robustness language: - iso: eng month: '09' oa: 1 oa_version: Published Version page: '446' project: - _id: 92099302-16d5-11f0-9cad-f9a785f54fbd name: 'Trustworthy Deep Learning Theory: Private Over-Parameterized Models and Robust LLMs' - _id: 911e6d1f-16d5-11f0-9cad-c5c68c6a1cdf grant_number: '101161364' name: 'Inference in High Dimensions: Light-speed Algorithms and Information Limits' - _id: 74caaef7-b034-11f1-8f2d-e0e993bb422e grant_number: COE12 name: Bilateral Artificial Intelligence (Mondelli) publication_identifier: isbn: - 978-3-99078-091-6 issn: - 2663-337X publication_status: published publisher: Institute of Science and Technology Austria related_material: record: - id: '12537' relation: part_of_dissertation status: public - id: '18972' relation: part_of_dissertation status: public - id: '18973' relation: part_of_dissertation status: public - id: '21324' relation: part_of_dissertation status: public - id: '22894' relation: part_of_dissertation status: public - id: '19627' relation: part_of_dissertation status: public - id: '12859' relation: part_of_dissertation status: public researchdata_availability: no status: public supervisor: - first_name: Marco full_name: Mondelli, Marco id: 27EB676C-8706-11E9-9510-7717E6697425 last_name: Mondelli orcid: 0000-0002-3242-7020 supplementarymaterial: no title: Trustworthy machine learning in high dimensions type: dissertation user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9 year: '2026' ... --- OA_place: publisher OA_type: gold _id: '22894' abstract: - lang: eng text: "Large-scale deep learning models are known to memorize parts of the training\r\nset. In machine learning theory, memorization is often framed as interpolation or\r\nlabel fitting, and classical results show that this can be achieved when the number\r\nof parameters p in the model is larger than the number of training samples n. In\r\nthis work, we consider memorization from the perspective of data reconstruction,\r\ndemonstrating that this can be achieved when p is larger than dn, where d is\r\nthe dimensionality of the data. More specifically, we show that, in the random\r\nfeatures model, when p ≫ dn, the subspace spanned by the training samples in\r\nfeature space gives sufficient information to identify the individual samples in input\r\nspace. Our analysis suggests an optimization method to reconstruct the dataset\r\nfrom the model parameters, and we demonstrate that this method performs well on\r\nvarious architectures (random features, two-layer fully-connected and deep residual\r\nnetworks). Our results reveal a law of data reconstruction, according to which the\r\nentire training dataset can be recovered as p exceeds the threshold dn.\r\n" acknowledgement: "M.M. is funded by the European Union (ERC, INF2\r\n, project number 101161364). S.B. was supported\r\nby a Google PhD fellowship. L.I. acknowledges the grant received from the European Union NextGenerationEU (Piano Nazionale di Ripresa E Resilienza (PNRR)) DM 351 on Trustworthy AI. T.T. &\r\nL.I. acknowledge the EU project ELSA - European Lighthouse on Secure and Safe AI. This study was\r\ncarried out within the FAIR - Future Artificial Intelligence Research and received funding from the\r\nEuropean Union Next-GenerationEU (PIANO NAZIONALE DI RIPRESA E RESILIENZA (PNRR)\r\n– MISSIONE 4 COMPONENTE 2, INVESTIMENTO 1.3 – D.D. 1555 11/10/2022, PE00000013).\r\nThis manuscript reflects only the authors’ views and opinions, neither the European Union nor the\r\nEuropean Commission can be considered responsible for them. The authors would like to thank\r\nYizhe Zhu for helpful discussions." article_processing_charge: No arxiv: 1 author: - first_name: Leonardo full_name: Iurada, Leonardo last_name: Iurada - first_name: Simone full_name: Bombari, Simone id: ca726dda-de17-11ea-bc14-f9da834f63aa last_name: Bombari - first_name: Tatiana full_name: Tommasi, Tatiana last_name: Tommasi - first_name: Marco full_name: Mondelli, Marco id: 27EB676C-8706-11E9-9510-7717E6697425 last_name: Mondelli orcid: 0000-0002-3242-7020 citation: ama: 'Iurada L, Bombari S, Tommasi T, Mondelli M. A law of data reconstruction for random features (and beyond). In: 14th International Conference on Learning Representations. Vol 2026. OpenReview; 2026:145275-145314.' apa: 'Iurada, L., Bombari, S., Tommasi, T., & Mondelli, M. (2026). A law of data reconstruction for random features (and beyond). In 14th International Conference on Learning Representations (Vol. 2026, pp. 145275–145314). Rio de Janeiro, Brazil: OpenReview.' chicago: Iurada, Leonardo, Simone Bombari, Tatiana Tommasi, and Marco Mondelli. “A Law of Data Reconstruction for Random Features (and Beyond).” In 14th International Conference on Learning Representations, 2026:145275–314. OpenReview, 2026. ieee: L. Iurada, S. Bombari, T. Tommasi, and M. Mondelli, “A law of data reconstruction for random features (and beyond),” in 14th International Conference on Learning Representations, Rio de Janeiro, Brazil, 2026, vol. 2026, pp. 145275–145314. ista: 'Iurada L, Bombari S, Tommasi T, Mondelli M. 2026. A law of data reconstruction for random features (and beyond). 14th International Conference on Learning Representations. ICLR: International Conference on Learning Representations vol. 2026, 145275–145314.' mla: Iurada, Leonardo, et al. “A Law of Data Reconstruction for Random Features (and Beyond).” 14th International Conference on Learning Representations, vol. 2026, OpenReview, 2026, pp. 145275–314. short: L. Iurada, S. Bombari, T. Tommasi, M. Mondelli, in:, 14th International Conference on Learning Representations, OpenReview, 2026, pp. 145275–145314. conference: end_date: 2026-04-27 location: Rio de Janeiro, Brazil name: 'ICLR: International Conference on Learning Representations ' start_date: 2026-04-23 corr_author: '1' das_tickbox: '0' date_created: 2026-09-09T13:31:46Z date_published: 2026-01-26T00:00:00Z date_updated: 2026-09-21T13:07:01Z day: '26' ddc: - '000' department: - _id: GradSch - _id: MaMo external_id: arxiv: - '2509.22214' file: - access_level: open_access checksum: a3dcba6649b7496124fa0ae68bf2c4cb content_type: application/pdf creator: cchlebak date_created: 2026-09-11T12:07:48Z date_updated: 2026-09-11T12:07:48Z file_id: '22907' file_name: 2026_ICLR_Iurada.pdf file_size: 7869510 relation: main_file success: 1 file_date_updated: 2026-09-11T12:07:48Z has_accepted_license: '1' intvolume: ' 2026' language: - iso: eng month: '01' oa: 1 oa_version: Published Version page: 145275-145314 project: - _id: 911e6d1f-16d5-11f0-9cad-c5c68c6a1cdf grant_number: '101161364' name: 'Inference in High Dimensions: Light-speed Algorithms and Information Limits' - _id: 92099302-16d5-11f0-9cad-f9a785f54fbd name: 'Trustworthy Deep Learning Theory: Private Over-Parameterized Models and Robust LLMs' publication: 14th International Conference on Learning Representations publication_identifier: isbn: - '9798331339678' publication_status: published publisher: OpenReview quality_controlled: '1' related_material: record: - id: '22857' relation: dissertation_contains status: public status: public title: A law of data reconstruction for random features (and beyond) 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: 8b945eb4-e2f2-11eb-945a-df72226e66a9 volume: 2026 year: '2026' ... --- OA_place: publisher OA_type: gold _id: '22921' abstract: - lang: eng text: 'Runtime monitoring of quantitative signals faces a fundamental trade-off between volatility and over-aggregation: instantaneous observations are noisy, while long-run averages obscure local structure. Localisation measures such as discounted averages offer a principled middle ground, yet remain poorly understood in runtime verification. This paper studies discounted sums from a monitoring perspective, in both deterministic and stochastic settings. We formalize the discounted monitoring problem and show that exact, sound monitoring of discounted sums cannot be achieved with finite memory. To overcome this impossibility, we introduce ε-approximately sound monitoring, deriving explicit bounds on memory and observation requirements. We then extend the framework to stochastic processes via expected discounted sums, defining pointwise and uniform (ε,δ)-soundness notions, establishing statistical optimality, and proving impossibility beyond a precision threshold. We also formalize the resource complexity of deterministic discounted monitoring via affine register machines and prove a tight worst-case lower bound. Finally, we present a specification language for arithmetic expressions over multiple discounted sums with synchronous and asynchronous semantics, and evaluate our approach on practical scenarios including algorithmic fairness.' acknowledgement: "This work has been supported by the European Research Council under Grant No.: ERC2020-AdG 101020093 and ERC-2021-AdG 101055412.\r\nFilip Cano: ERC-2020-AdG 101020093\r\nThomas A. Henzinger: ERC-2020-AdG 101020093\r\nKonstantin Kueffner: ERC-2020-AdG 101020093\r\nN. Ege Saraç: ERC-2021-AdG 101055412" alternative_title: - LIPIcs article_number: 22:1-22:19 article_processing_charge: Yes arxiv: 1 author: - first_name: Filip full_name: Cano Cordoba, Filip id: 708cad98-e86a-11ef-8098-bdae2d7c6af1 last_name: Cano Cordoba orcid: 0000-0002-0783-904X - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000-0002-2985-7724 - first_name: Konstantin full_name: Kueffner, Konstantin id: 8121a2d0-dc85-11ea-9058-af578f3b4515 last_name: Kueffner orcid: 0000-0001-8974-2542 - first_name: Naci E full_name: Sarac, Naci E id: 8C6B42F8-C8E6-11E9-A03A-F2DCE5697425 last_name: Sarac citation: ama: 'Cano Cordoba F, Henzinger TA, Kueffner K, Sarac NE. Monitoring discounted sum properties. In: 37th International Conference on Concurrency Theory. Vol 391. Schloss Dagstuhl - Leibniz-Zentrum für Informatik; 2026. doi:10.4230/LIPIcs.CONCUR.2026.22' apa: 'Cano Cordoba, F., Henzinger, T. A., Kueffner, K., & Sarac, N. E. (2026). Monitoring discounted sum properties. In 37th International Conference on Concurrency Theory (Vol. 391). Liverpool, United Kingdom: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.CONCUR.2026.22' chicago: Cano Cordoba, Filip, Thomas A Henzinger, Konstantin Kueffner, and Naci E Sarac. “Monitoring Discounted Sum Properties.” In 37th International Conference on Concurrency Theory, Vol. 391. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2026. https://doi.org/10.4230/LIPIcs.CONCUR.2026.22. ieee: F. Cano Cordoba, T. A. Henzinger, K. Kueffner, and N. E. Sarac, “Monitoring discounted sum properties,” in 37th International Conference on Concurrency Theory, Liverpool, United Kingdom, 2026, vol. 391. ista: 'Cano Cordoba F, Henzinger TA, Kueffner K, Sarac NE. 2026. Monitoring discounted sum properties. 37th International Conference on Concurrency Theory. CONCUR: Conference on Concurrency Theory, LIPIcs, vol. 391, 22:1-22:19.' mla: Cano Cordoba, Filip, et al. “Monitoring Discounted Sum Properties.” 37th International Conference on Concurrency Theory, vol. 391, 22:1-22:19, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2026, doi:10.4230/LIPIcs.CONCUR.2026.22. short: F. Cano Cordoba, T.A. Henzinger, K. Kueffner, N.E. Sarac, in:, 37th International Conference on Concurrency Theory, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2026. conference: end_date: 2026-09-04 location: Liverpool, United Kingdom name: 'CONCUR: Conference on Concurrency Theory' start_date: 2026-09-01 corr_author: '1' das_tickbox: '1' dataavailabilitystatement: "Software (Source Code): https://github.com/filipcano/monitoringdiscounted-sum-properties [10]\r\narchived at swh:1:dir:cb99396415f279c985cd05206b44320227f64245\r\n" date_created: 2026-09-13T22:01:54Z date_published: 2026-08-24T00:00:00Z date_updated: 2026-09-22T06:02:06Z day: '24' ddc: - '000' department: - _id: ToHe - _id: GradSch doi: 10.4230/LIPIcs.CONCUR.2026.22 ec_funded: 1 external_id: arxiv: - '2606.25979' file: - access_level: open_access checksum: f7b2e22428344fd7972c54f099df6aba content_type: application/pdf creator: dernst date_created: 2026-09-22T05:59:03Z date_updated: 2026-09-22T05:59:03Z file_id: '22978' file_name: 2026_LIPIcsCONCUR_Cano.pdf file_size: 997156 relation: main_file success: 1 file_date_updated: 2026-09-22T05:59:03Z fulldoi: https://doi.org/10.4230/LIPIcs.CONCUR.2026.22 has_accepted_license: '1' intvolume: ' 391' keyword: - Runtime Verification - Probabilistic Systems - Quantitative Verification - Approximate Monitoring language: - iso: eng month: '08' oa: 1 oa_version: Published Version project: - _id: 62781420-2b32-11ec-9570-8d9b63373d4d call_identifier: H2020 grant_number: '101020093' name: Vigilant Algorithmic Monitoring of Software publication: 37th International Conference on Concurrency Theory publication_identifier: isbn: - '9783959774475' issn: - 1868-8969 publication_status: published publisher: Schloss Dagstuhl - Leibniz-Zentrum für Informatik quality_controlled: '1' researchdata_availability: no scopus_import: '1' status: public supplementarymaterial: no title: Monitoring discounted sum properties 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: 391 year: '2026' ... --- OA_place: repository _id: '22777' acknowledged_ssus: - _id: Bio - _id: LifeSc article_processing_charge: No author: - first_name: Xin full_name: Tong, Xin id: 50F65CDC-AA30-11E9-A72B-8A12E6697425 last_name: Tong citation: ama: Tong X. Towards a deeper understanding of meroblastic cleavage - supplementary movies. 2026. doi:10.15479/AT-ISTA-22777 apa: Tong, X. (2026). Towards a deeper understanding of meroblastic cleavage - supplementary movies. Institute of Science and Technology Austria. https://doi.org/10.15479/AT-ISTA-22777 chicago: Tong, Xin. “Towards a Deeper Understanding of Meroblastic Cleavage - Supplementary Movies.” Institute of Science and Technology Austria, 2026. https://doi.org/10.15479/AT-ISTA-22777. ieee: X. Tong, “Towards a deeper understanding of meroblastic cleavage - supplementary movies.” Institute of Science and Technology Austria, 2026. ista: Tong X. 2026. Towards a deeper understanding of meroblastic cleavage - supplementary movies, Institute of Science and Technology Austria, 10.15479/AT-ISTA-22777. mla: Tong, Xin. Towards a Deeper Understanding of Meroblastic Cleavage - Supplementary Movies. Institute of Science and Technology Austria, 2026, doi:10.15479/AT-ISTA-22777. short: X. Tong, (2026). corr_author: '1' date_created: 2026-09-03T10:48:15Z date_published: 2026-09-04T00:00:00Z date_updated: 2026-09-28T09:49:39Z day: '4' department: - _id: GradSch - _id: CaHe doi: 10.15479/AT-ISTA-22777 doi_confirm: '1' ec_funded: 1 file: - access_level: open_access checksum: ba2d20babb1a8e437b41c513c4d226a4 content_type: text/plain creator: xtong date_created: 2026-09-03T10:47:23Z date_updated: 2026-09-03T10:47:23Z file_id: '22779' file_name: README.txt file_size: 223 relation: main_file success: 1 - access_level: open_access checksum: 59565d43eca072572e37c81d640b8450 content_type: video/avi creator: xtong date_created: 2026-09-03T10:53:55Z date_updated: 2026-09-03T10:53:55Z file_id: '22780' file_name: Movie S1_brightfield.avi file_size: 1137586 relation: main_file success: 1 - access_level: open_access checksum: 2c0740d4555b308e3248f1695042df7b content_type: video/avi creator: xtong date_created: 2026-09-03T10:58:05Z date_updated: 2026-09-03T10:58:05Z file_id: '22796' file_name: Movie S2_membrane.avi file_size: 2400912 relation: main_file success: 1 - 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access_level: open_access checksum: 343f8d51cd1ff3f8bbdbbc0a86e7117f content_type: video/avi creator: xtong date_created: 2026-09-03T10:57:20Z date_updated: 2026-09-03T10:57:20Z file_id: '22793' file_name: Movie S15_Cdh1_Factin.avi file_size: 3399188 relation: main_file success: 1 - access_level: open_access checksum: a48d888dc7994e54390c55deb0976f5a content_type: video/avi creator: xtong date_created: 2026-09-03T10:57:21Z date_updated: 2026-09-03T10:57:21Z file_id: '22794' file_name: Movie S16_cafree.avi file_size: 1253862 relation: main_file success: 1 - access_level: open_access checksum: ac4790a151352cc72534ec55468acebe content_type: video/avi creator: xtong date_created: 2026-09-03T10:57:22Z date_updated: 2026-09-03T10:57:22Z file_id: '22795' file_name: Movie S17_carhoa.avi file_size: 2268762 relation: main_file success: 1 file_date_updated: 2026-09-03T10:58:05Z fulldoi: https://doi.org/10.15479/AT-ISTA-22777 has_accepted_license: '1' month: '9' oa: 1 oa_version: None project: - _id: 9B861AAC-BA93-11EA-9121-9846C619BF3A name: NOMIS Fellowship Program - _id: 05943252-7A3F-11EA-A408-12923DDC885E call_identifier: H2020 grant_number: '851288' name: Design Principles of Branching Morphogenesis publisher: Institute of Science and Technology Austria related_material: record: - id: '22804' relation: used_in_publication status: for_moderation status: public title: Towards a deeper understanding of meroblastic cleavage - supplementary movies 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: research_data user_id: 68b8ca59-c5b3-11ee-8790-cd641c68093d year: '2026' ... --- DOAJ_listed: '1' OA_place: publisher OA_type: gold _id: '22957' abstract: - lang: eng text: Linguistic inequality remains a silent barrier in contemporary science, particularly in rapidly evolving and interdisciplinary fields such as bioinformatics. This article examines how the Spanish-speaking community has responded to this gap through the creation of the Simposio de Estudiantes Hispanohablantes de Bioinformática y Biología Computacional (SEH2Bioinfo), a collective initiative that transforms language into a tool for inclusion and collaboration. Drawing on a historical review of the use of Spanish in scientific communication and an analysis of the two editions of SEH2Bioinfo (2022 and 2025), complemented by surveys of more than 1500 participants, we explore the effects of language on confidence, participation, and academic visibility. The findings show that Spanish can serve as a space for training and mentorship without compromising rigor, while simultaneously strengthening international networks and promoting open science. The growth of SEH2Bioinfo, its collaborative approach, and its intercontinental reach establish the symposium as a model for linguistic equity in scientific practice. Its experience demonstrates that expanding linguistic diversity in bioinformatics is not only possible but essential to building a global scientific community that is fairer, more connected, and representative. acknowledgement: "We acknowledge the sponsors who made the SEH2Bioinfo possible, the organizers from the various Spanish-speaking RSGs, and\r\nthe collaborators who contributed to dissemination, logistics,\r\nand other essential tasks for its execution. G.J.O.-O. thanks the\r\nFONDECYT Postdoctoral Project No. 3250793 for financial support. G.J.O.-O. also expresses gratitude to Valentina Luza: “May\r\nher passion for science communication keep inspiring new generations, myself included, to infinity and beyond!” R.G.P.\r\nthanks the Argentinian public university education system as an\r\nelement of social ascendance and democratization of professional opportunities." article_number: vbag182 article_processing_charge: Yes article_type: original author: - first_name: Carla L full_name: Padilla Franzotti, Carla L last_name: Padilla Franzotti - first_name: Gabriel J full_name: Olguín-Orellana, Gabriel J last_name: Olguín-Orellana - first_name: Nicolas full_name: Palopoli, Nicolas last_name: Palopoli - first_name: Sebastián full_name: Urquiza-Zurich, Sebastián last_name: Urquiza-Zurich - first_name: Adrian full_name: Garcia-Moreno, Adrian last_name: Garcia-Moreno - first_name: Sara full_name: Monzón, Sara last_name: Monzón - first_name: Mónica full_name: Cabrera-Pasadas, Mónica last_name: Cabrera-Pasadas - first_name: Irene full_name: Soler Sáez, Irene last_name: Soler Sáez - first_name: Carla full_name: Perpiñá-Clérigues, Carla last_name: Perpiñá-Clérigues - first_name: Rafael J full_name: Puche Quiñonez, Rafael J last_name: Puche Quiñonez - first_name: Jennifer full_name: Vélez Segura, Jennifer last_name: Vélez Segura - first_name: Jose Abel full_name: Lovaco-Flores, Jose Abel last_name: Lovaco-Flores - first_name: Cleidy M full_name: Osorio Mogollón, Cleidy M last_name: Osorio Mogollón - first_name: Eva M full_name: Esquinas-Román, Eva M last_name: Esquinas-Román - first_name: Maria C full_name: Miserendino, Maria C id: 273e0cbd-72f0-11ef-b75a-f9f932e292fa last_name: Miserendino - first_name: Pradeep full_name: Eranti, Pradeep last_name: Eranti - first_name: Ana full_name: Castillo-Orozco, Ana last_name: Castillo-Orozco - first_name: Yesid full_name: Cuesta-Astroz, Yesid last_name: Cuesta-Astroz - first_name: R Gonzalo full_name: Parra, R Gonzalo last_name: Parra citation: ama: 'Padilla Franzotti CL, Olguín-Orellana GJ, Palopoli N, et al. Bioinformatics in Español: Expanding open, diverse, and collaborative science through SEH2Bioinfo. Bioinformatics Advances. 2026;6(1). doi:10.1093/bioadv/vbag182' apa: 'Padilla Franzotti, C. L., Olguín-Orellana, G. J., Palopoli, N., Urquiza-Zurich, S., Garcia-Moreno, A., Monzón, S., … Parra, R. G. (2026). Bioinformatics in Español: Expanding open, diverse, and collaborative science through SEH2Bioinfo. Bioinformatics Advances. Oxford University Press. https://doi.org/10.1093/bioadv/vbag182' chicago: 'Padilla Franzotti, Carla L, Gabriel J Olguín-Orellana, Nicolas Palopoli, Sebastián Urquiza-Zurich, Adrian Garcia-Moreno, Sara Monzón, Mónica Cabrera-Pasadas, et al. “Bioinformatics in Español: Expanding Open, Diverse, and Collaborative Science through SEH2Bioinfo.” Bioinformatics Advances. Oxford University Press, 2026. https://doi.org/10.1093/bioadv/vbag182.' ieee: 'C. L. Padilla Franzotti et al., “Bioinformatics in Español: Expanding open, diverse, and collaborative science through SEH2Bioinfo,” Bioinformatics Advances, vol. 6, no. 1. Oxford University Press, 2026.' ista: 'Padilla Franzotti CL, Olguín-Orellana GJ, Palopoli N, Urquiza-Zurich S, Garcia-Moreno A, Monzón S, Cabrera-Pasadas M, Soler Sáez I, Perpiñá-Clérigues C, Puche Quiñonez RJ, Vélez Segura J, Lovaco-Flores JA, Osorio Mogollón CM, Esquinas-Román EM, Miserendino MC, Eranti P, Castillo-Orozco A, Cuesta-Astroz Y, Parra RG. 2026. Bioinformatics in Español: Expanding open, diverse, and collaborative science through SEH2Bioinfo. Bioinformatics Advances. 6(1), vbag182.' mla: 'Padilla Franzotti, Carla L., et al. “Bioinformatics in Español: Expanding Open, Diverse, and Collaborative Science through SEH2Bioinfo.” Bioinformatics Advances, vol. 6, no. 1, vbag182, Oxford University Press, 2026, doi:10.1093/bioadv/vbag182.' short: C.L. Padilla Franzotti, G.J. Olguín-Orellana, N. Palopoli, S. Urquiza-Zurich, A. Garcia-Moreno, S. Monzón, M. Cabrera-Pasadas, I. Soler Sáez, C. Perpiñá-Clérigues, R.J. Puche Quiñonez, J. Vélez Segura, J.A. Lovaco-Flores, C.M. Osorio Mogollón, E.M. Esquinas-Román, M.C. Miserendino, P. Eranti, A. Castillo-Orozco, Y. Cuesta-Astroz, R.G. Parra, Bioinformatics Advances 6 (2026). das_tickbox: '1' dataavailabilitystatement: "The data underlying this article, including the abstract books for\r\nthe first and second editions of the SEH2Bioinfo symposia, are\r\navailable in Zenodo at https://doi.org/10.5281/zenodo.6603621\r\nand https://doi.org/10.5281/zenodo.1,54,46,570, respectively." date_created: 2026-09-17T11:06:17Z date_published: 2026-08-06T00:00:00Z date_updated: 2026-10-01T08:59:32Z day: '06' ddc: - '570' department: - _id: PaSc - _id: GradSch doi: 10.1093/bioadv/vbag182 external_id: pmid: - '42577783' file: - access_level: open_access checksum: 8885b0531a655103c46899b2f935b0db content_type: application/pdf creator: dernst date_created: 2026-10-01T08:55:00Z date_updated: 2026-10-01T08:55:00Z file_id: '23016' file_name: 2026_BioinformaticsAdvances_Franzotti.pdf file_size: 1359968 relation: main_file success: 1 file_date_updated: 2026-10-01T08:55:00Z fulldoi: https://doi.org/10.1093/bioadv/vbag182 has_accepted_license: '1' intvolume: ' 6' issue: '1' language: - iso: eng month: '08' oa: 1 oa_version: Published Version pmid: 1 publication: Bioinformatics Advances publication_identifier: eissn: - 2635-0041 publication_status: published publisher: Oxford University Press quality_controlled: '1' related_material: link: - relation: erratum url: https://doi.org/10.1093/bioadv/vbag271 researchdata_availability: yes scopus_import: '1' status: public supplementarymaterial: no title: 'Bioinformatics in Español: Expanding open, diverse, and collaborative science through SEH2Bioinfo' 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: 6 year: '2026' ... --- OA_place: publisher _id: '21198' abstract: - lang: eng text: "In recent years there has been a massive increase in the amount of data generated in a\r\ndecentralized manner. Ever more powerful edge devices, such as smartphones, have become\r\nubiquitous in most societies on earth. Through text typed, photos taken and apps used,\r\nthese devices, which we refer to as clients, generate enormous amounts of high quality and\r\ncomplex data. Moreover, the nature of these devices means the data they generate is often\r\nsensitive and privacy concerns prevent it being gathered and stored in a central location. This\r\npresents a challenge to the modern machine learning paradigm that requires central access\r\nto large amounts of data. Federated learning (FL) has emerged as one of the answers to\r\nthis problem. Rather than bringing the data to the model, FL sends the model to the data.\r\nModel training takes place on device, with periodically synchronized updates, allowing data to\r\nremain locally stored. While this approach offers significant privacy advantages it comes with\r\nits own set of unique challenges. These include: data heterogeneity, the notion that different\r\ndevices generate data in distinct ways which can negatively impact training dynamics; systems\r\nheterogeneity, meaning that different devices may have differing hardware specifications; high\r\ncommunication costs, which are induced by the repeated transferring of models over the\r\nnetwork and low device computational power, which limits the use of larger models on device.\r\nIn this thesis we present a range of methods for federated learning. We focus primarily on\r\nthe challenge of data heterogeneity, though the methods presented are designed to be well\r\nadapted to the other challenges of a federated setting, such as the constraints of limited\r\ncompute and communication overhead. We first present a method for explicitly modeling client\r\ndata heterogeneity. The approach formulates clients as samples from a certain probability\r\ndistribution and infers the parameters of this distribution from the available training clients.\r\nThis learned distribution then represents the heterogeneity present among the clients and can\r\nbe sampled from in order to create new simulated clients that are similar to the real clients we\r\nhave observed so far. Following this we present two methods for directly dealing with data\r\nheterogeneity through personalization. Highly heterogeneous client data distributions can mean\r\nthat learning a single global model becomes suboptimal, and some form of personalization of\r\nmodels to each individual client is required. Our approaches are based around hypernetworks,\r\nwhich we use to generate personalized model parameters without the need for additional\r\ntraining or finetuning. In the first approach we focus on generating full parameterizations of\r\nclient models using learned embeddings of client data and labels, with a hypernetwork located\r\non the central server. In the second approach we address the more challenging scenario where\r\nwe want to generate a personalized model for a client without any label information. The\r\nhypernetwork is trained to generate a low dimensional representation of a client’s personalized\r\nmodel parameters, allowing it to be transferred to and run on the client devices. In our final\r\npresented method, we change our focus and rather than aim to directly address the challenge\r\nof data heterogeneity, we instead ensure we are unaffected by it. This is done in the context\r\nof k-means clustering and we present a method for federated clustering with a focus on added\r\nprivacy guarantees." acknowledged_ssus: - _id: ScienComp acknowledgement: "This research was funded in part by the Austrian Science Fund (FWF)\r\n[10.55776/COE12]. Furthermore, the candidate acknowledges the support from the Scientific\r\nService Units (SSU) of ISTA through resources provided by Scientific Computing (SciComp)." alternative_title: - ISTA Thesis article_processing_charge: No author: - first_name: Jonathan A full_name: Scott, Jonathan A id: e499926b-f6e0-11ea-865d-9c63db0031e8 last_name: Scott citation: ama: Scott JA. Data heterogeneity and personalization in federated learning. 2026. doi:10.15479/AT-ISTA-21198 apa: Scott, J. A. (2026). Data heterogeneity and personalization in federated learning. Institute of Science and Technology Austria. https://doi.org/10.15479/AT-ISTA-21198 chicago: Scott, Jonathan A. “Data Heterogeneity and Personalization in Federated Learning.” Institute of Science and Technology Austria, 2026. https://doi.org/10.15479/AT-ISTA-21198. ieee: J. A. Scott, “Data heterogeneity and personalization in federated learning,” Institute of Science and Technology Austria, 2026. ista: Scott JA. 2026. Data heterogeneity and personalization in federated learning. Institute of Science and Technology Austria. mla: Scott, Jonathan A. Data Heterogeneity and Personalization in Federated Learning. Institute of Science and Technology Austria, 2026, doi:10.15479/AT-ISTA-21198. short: J.A. Scott, Data Heterogeneity and Personalization in Federated Learning, Institute of Science and Technology Austria, 2026. corr_author: '1' date_created: 2026-02-09T14:59:53Z date_published: 2026-02-09T00:00:00Z date_updated: 2026-10-01T09:29:03Z day: '09' ddc: - '005' degree_awarded: PhD department: - _id: GradSch - _id: ChLa doi: 10.15479/AT-ISTA-21198 doi_confirm: '1' file: - access_level: closed checksum: 121c1d968bd86f3630aa7e81d5bbbcb0 content_type: application/zip creator: jscott date_created: 2026-02-17T11:46:22Z date_updated: 2026-02-17T11:46:22Z file_id: '21298' file_name: 2026_Scott_Jonathan_Thesis_Source.zip file_size: 272379252 relation: source_file - access_level: open_access checksum: 6e3e08ba474bbee8511cc8a839ab2077 content_type: application/pdf creator: jscott date_created: 2026-02-27T10:25:41Z date_updated: 2026-02-27T10:25:41Z file_id: '21366' file_name: 2026_Jonathan_Scott_Thesis.pdf file_size: 15220298 relation: main_file success: 1 file_date_updated: 2026-02-27T10:25:41Z fulldoi: https://doi.org/10.15479/AT-ISTA-21198 has_accepted_license: '1' language: - iso: eng month: '02' oa: 1 oa_version: Published Version page: '158' project: - _id: d8f03aaa-b035-11f1-8588-d5147fa879e0 grant_number: COE12 name: Bilateral Artificial Intelligence (Lampert) publication_identifier: issn: - 2663-337X publication_status: published publisher: Institute of Science and Technology Austria related_material: record: - id: '21207' relation: part_of_dissertation status: public - id: '20819' relation: part_of_dissertation status: public - id: '17411' relation: part_of_dissertation status: public - id: '18120' relation: part_of_dissertation status: public status: public supervisor: - first_name: Christoph full_name: Lampert, Christoph id: 40C20FD2-F248-11E8-B48F-1D18A9856A87 last_name: Lampert orcid: 0000-0001-8622-7887 title: Data heterogeneity and personalization in federated learning type: dissertation user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2026' ... --- OA_place: publisher _id: '21854' abstract: - lang: eng text: "As neural-network-based models grow both in size and popularity, interest has grown in making the models smaller and more efficient to train. To that end, many methods have been proposed to prune models by reducing their number of nonzero parameters. Additionally, parameter-efficient fine-tuning, in which a much smaller number of parameters than the total contained in the model is updated during training, has become very popular, especially in the space of Large Language Models. At the same time, the increasingly routine deployment of machine learning in real-world applications has spurred a drive to make them more trustworthy - in the sense of, among other things, being unbiased, interpretable, and editable. In this thesis, we examine the interplay between efficiency and trustworthiness.\r\n\r\nFirst, we analyze the effects of model pruning on bias in computer vision models, demonstrating that increased sparsity leads to greater bias, largely as a function of increased model uncertainty in marginal cases. Based on this observation, we propose several bias mitigation techniques. Then, we demonstrate that example-specific model pruning can improve model interpretation methods while improving pruning efficiency to make example-specific model pruning feasible in real time. Then, we investigate the effectiveness of parameter-efficient and data-efficient model personalization via fine-tuning, demonstrating that it is highly feasible with very small computational and data resources. Finally, we consider efficiency in editing model knowledge using a custom synthetic data framework, demonstrating that parameter-efficient, low-rank fine-tuning frequently outperforms full-rank fine-tuning, and, additionally, that restricting which model blocks are fine-tuned frequently improves results. Together, the results in this thesis provide new insights and techniques for combining trustworthiness and efficiency during neural network inference and training.\r\n\r\n" acknowledged_ssus: - _id: ScienComp acknowledgement: "The research in this Ph.D. was funded in whole\r\nor in part by the Austrian Science Fund (FWF) W1260-N35 (Vienna Graduate School for\r\nComputational Optimization). For open access purposes the author has applied a CC BY\r\npublic copyright license to any author accepted manuscript version arising from this submission\r\nwherever possible. Additionally, I am grateful to Alois Schlögl, Waleed Khalid, and the rest of\r\nthe ISTA Scientific Computing team for building and maintaining the infrastructure I used\r\nto run experiments. I’m also deeply grateful to the Alistarh group’s administrative assistant,\r\nChristine Francois, who always deals with our nonsense with common sense and a smile.\r\n" alternative_title: - ISTA Thesis article_processing_charge: No author: - first_name: Eugenia B full_name: Iofinova, Eugenia B id: f9a17499-f6e0-11ea-865d-fdf9a3f77117 last_name: Iofinova orcid: 0000-0002-7778-3221 citation: ama: Iofinova EB. On the utility and effects of efficiency in artificial neural networks. 2026. doi:10.15479/AT-ISTA-21854 apa: Iofinova, E. B. (2026). On the utility and effects of efficiency in artificial neural networks. Institute of Science and Technology Austria. https://doi.org/10.15479/AT-ISTA-21854 chicago: Iofinova, Eugenia B. “On the Utility and Effects of Efficiency in Artificial Neural Networks.” Institute of Science and Technology Austria, 2026. https://doi.org/10.15479/AT-ISTA-21854. ieee: E. B. Iofinova, “On the utility and effects of efficiency in artificial neural networks,” Institute of Science and Technology Austria, 2026. ista: Iofinova EB. 2026. On the utility and effects of efficiency in artificial neural networks. Institute of Science and Technology Austria. mla: Iofinova, Eugenia B. On the Utility and Effects of Efficiency in Artificial Neural Networks. Institute of Science and Technology Austria, 2026, doi:10.15479/AT-ISTA-21854. short: E.B. Iofinova, On the Utility and Effects of Efficiency in Artificial Neural Networks, Institute of Science and Technology Austria, 2026. corr_author: '1' das_tickbox: '1' date_created: 2026-05-11T08:43:22Z date_published: 2026-05-11T00:00:00Z date_updated: 2026-10-01T09:32:47Z day: '11' ddc: - '000' degree_awarded: PhD department: - _id: GradSch - _id: DaAl doi: 10.15479/AT-ISTA-21854 doi_confirm: '1' file: - access_level: closed checksum: 2e148dad920e3f9b7c32796e0ba2e5f7 content_type: application/zip creator: eiofinov date_created: 2026-05-11T08:36:01Z date_updated: 2026-05-11T08:36:01Z file_id: '21856' file_name: EIofinova_thesis_FinalVersion.zip file_size: 28479571 relation: source_file - access_level: open_access checksum: b10c2933f386f532b2dbf28b19c5525c content_type: application/pdf creator: eiofinov date_created: 2026-05-13T13:10:48Z date_updated: 2026-05-13T13:10:48Z file_id: '21877' file_name: 2026_Iofinova_Eugenia_Thesis.pdf file_size: 18137757 relation: main_file success: 1 file_date_updated: 2026-05-13T13:10:48Z fulldoi: https://doi.org/10.15479/AT-ISTA-21854 has_accepted_license: '1' language: - iso: eng month: '05' oa: 1 oa_version: Published Version page: '237' project: - _id: 9B9290DE-BA93-11EA-9121-9846C619BF3A grant_number: W1260-N35 name: Vienna Graduate School on Computational Optimization publication_identifier: issn: - 2663-337X publication_status: published publisher: Institute of Science and Technology Austria publisher_comment: In reference to IEEE copyrighted material which is used with permission in this thesis, the IEEE does not endorse any of ISTA's products or services. Internal or personal use of this material is permitted. If interested in reprinting/republishing IEEE copyrighted material for advertising or promotional purposes or for creating new collective works for resale or redistribution, please go to http://www.ieee.org/publications_standards/publications/rights/rights_link.html to learn how to obtain a License from RightsLink. If applicable, University Microfilms and/or ProQuest Library, or the Archives of Canada may supply single copies of the dissertation. related_material: record: - id: '14771' relation: part_of_dissertation status: public - id: '21858' relation: part_of_dissertation status: public - id: '21859' relation: part_of_dissertation status: public - id: '21857' relation: part_of_dissertation status: public - id: '18121' relation: part_of_dissertation status: public status: public supervisor: - first_name: Dan-Adrian full_name: Alistarh, Dan-Adrian id: 4A899BFC-F248-11E8-B48F-1D18A9856A87 last_name: Alistarh orcid: 0000-0003-3650-940X title: On the utility and effects of efficiency in artificial neural networks type: dissertation user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9 year: '2026' ... --- OA_place: publisher OA_type: hybrid PlanS_conform: '1' _id: '21982' abstract: - lang: eng text: A floating Leidenfrost droplet exhibits curvature inversion of its underside, due to the balance of vapor pressure and surface tension. Using interferometric imaging, we find different behavior for a levitated hydrogel sphere. Curvature inversion is observed briefly just after deposition, but quickly gives way to a steady state with no inversion. We show the essential role of vaporization in shaping the underbelly of the hydrogel, where changes due to direct mass loss are more significant than the balance of vapor pressure and elastic forces. acknowledged_ssus: - _id: M-Shop - _id: ScienComp acknowledgement: 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 Facility. J.B. acknowledges funding from the European Union's Horizon research and innovation programme under the Marie Sklodowska-Curie Grant Agreement No. 101106500. article_number: L053502 article_processing_charge: Yes (via OA deal) article_type: letter_note arxiv: 1 author: - first_name: Vicente L full_name: Diaz Melian, Vicente L id: b6798902-eea0-11ea-9cbc-a8e14286c631 last_name: Diaz Melian - 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: Jack full_name: Binysh, Jack last_name: Binysh - first_name: Anton full_name: Souslov, Anton last_name: Souslov - 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: Diaz Melian VL, Lenton IC, Binysh J, Souslov A, Waitukaitis SR. Geometry of the vapor layer under a Leidenfrost hydrogel sphere. Physical Review E. 2026;113(5). doi:10.1103/m7gr-2t6j apa: Diaz Melian, V. L., Lenton, I. C., Binysh, J., Souslov, A., & Waitukaitis, S. R. (2026). Geometry of the vapor layer under a Leidenfrost hydrogel sphere. Physical Review E. American Physical Society. https://doi.org/10.1103/m7gr-2t6j chicago: Diaz Melian, Vicente L, Isaac C Lenton, Jack Binysh, Anton Souslov, and Scott R Waitukaitis. “Geometry of the Vapor Layer under a Leidenfrost Hydrogel Sphere.” Physical Review E. American Physical Society, 2026. https://doi.org/10.1103/m7gr-2t6j. ieee: V. L. Diaz Melian, I. C. Lenton, J. Binysh, A. Souslov, and S. R. Waitukaitis, “Geometry of the vapor layer under a Leidenfrost hydrogel sphere,” Physical Review E, vol. 113, no. 5. American Physical Society, 2026. ista: Diaz Melian VL, Lenton IC, Binysh J, Souslov A, Waitukaitis SR. 2026. Geometry of the vapor layer under a Leidenfrost hydrogel sphere. Physical Review E. 113(5), L053502. mla: Diaz Melian, Vicente L., et al. “Geometry of the Vapor Layer under a Leidenfrost Hydrogel Sphere.” Physical Review E, vol. 113, no. 5, L053502, American Physical Society, 2026, doi:10.1103/m7gr-2t6j. short: V.L. Diaz Melian, I.C. Lenton, J. Binysh, A. Souslov, S.R. Waitukaitis, Physical Review E 113 (2026). corr_author: '1' date_created: 2026-06-10T07:36:41Z date_published: 2026-05-14T00:00:00Z date_updated: 2026-10-02T08:44:47Z day: '14' ddc: - '530' department: - _id: ScWa - _id: GradSch doi: 10.1103/m7gr-2t6j external_id: arxiv: - '2507.04982' file: - access_level: open_access checksum: 902cc8d177c8d3ae9cfe07c30375c9a9 content_type: application/pdf creator: dernst date_created: 2026-06-16T11:21:53Z date_updated: 2026-06-16T11:21:53Z file_id: '22014' file_name: 2026_PhysicalReviewE_DiazMelian.pdf file_size: 3173197 relation: main_file success: 1 file_date_updated: 2026-06-16T11:21:53Z fulldoi: https://doi.org/10.1103/m7gr-2t6j has_accepted_license: '1' intvolume: ' 113' issue: '5' language: - iso: eng month: '05' oa: 1 oa_version: Published Version publication: Physical Review E publication_identifier: eissn: - 2470-0053 issn: - 2470-0045 publication_status: published publisher: American Physical Society quality_controlled: '1' related_material: record: - id: '23005' relation: dissertation_contains status: public scopus_import: '1' status: public title: Geometry of the vapor layer under a Leidenfrost hydrogel sphere 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: 113 year: '2026' ... --- OA_place: publisher _id: '23005' abstract: - lang: eng text: When a Leidenfrost droplet floats on its own vapor layer, the interplay between vapor pressure, surface tension, and gravity determines its shape, and in the stable regime the underside of the droplet exhibits curvature inversion. Using interferometric imaging, we observe a different behavior for a levitated hydrogel sphere. Curvature inversion appears briefly after deposition, but the continuous vaporization process removes this feature, leading first to an oscillatory regime and eventually to a steady state without curvature inversion. We demonstrate the essential role of vaporization in shaping the hydrogel underbelly, where direct mass loss has a stronger influence than the balance between vapor pressure and elastic forces. acknowledged_ssus: - _id: M-Shop alternative_title: - ISTA Thesis article_processing_charge: No author: - first_name: Vicente L full_name: Diaz Melian, Vicente L id: b6798902-eea0-11ea-9cbc-a8e14286c631 last_name: Diaz Melian citation: ama: Diaz Melian VL. The morphology underneath a levitated hydrogel sphere. 2026. doi:10.15479/AT-ISTA-23005 apa: Diaz Melian, V. L. (2026). The morphology underneath a levitated hydrogel sphere. Institute of Science and Technology Austria. https://doi.org/10.15479/AT-ISTA-23005 chicago: Diaz Melian, Vicente L. “The Morphology underneath a Levitated Hydrogel Sphere.” Institute of Science and Technology Austria, 2026. https://doi.org/10.15479/AT-ISTA-23005. ieee: V. L. Diaz Melian, “The morphology underneath a levitated hydrogel sphere,” Institute of Science and Technology Austria, 2026. ista: Diaz Melian VL. 2026. The morphology underneath a levitated hydrogel sphere. Institute of Science and Technology Austria. mla: Diaz Melian, Vicente L. The Morphology underneath a Levitated Hydrogel Sphere. Institute of Science and Technology Austria, 2026, doi:10.15479/AT-ISTA-23005. short: V.L. Diaz Melian, The Morphology underneath a Levitated Hydrogel Sphere, Institute of Science and Technology Austria, 2026. corr_author: '1' date_created: 2026-09-28T17:40:23Z date_published: 2026-09-29T00:00:00Z date_updated: 2026-10-02T08:44:47Z day: '29' ddc: - '530' - '530' - '530' degree_awarded: PhD department: - _id: GradSch - _id: ScWa doi: 10.15479/AT-ISTA-23005 doi_confirm: '1' file: - access_level: open_access checksum: f339bdee0a6925573687de928ca525dc content_type: application/pdf creator: vdiazmel date_created: 2026-09-29T09:22:27Z date_updated: 2026-09-29T09:56:46Z file_id: '23007' file_name: 2026_diaz-melian_vicente_Thesis.pdf file_size: 8463804 relation: main_file - access_level: closed checksum: 5b17122895fc419bfb620e23bfe7780a content_type: application/zip creator: vdiazmel date_created: 2026-09-29T09:49:32Z date_updated: 2026-09-29T09:56:46Z file_id: '23008' file_name: 2026_diaz-melian_vicente_Thesis.zip file_size: 4028974886 relation: source_file file_date_updated: 2026-09-29T09:56:46Z fulldoi: https://doi.org/10.15479/AT-ISTA-23005 has_accepted_license: '1' language: - iso: eng month: '09' oa: 1 oa_version: Published Version page: '114' publication_identifier: issn: - 2663-337X publication_status: published publisher: Institute of Science and Technology Austria related_material: record: - id: '14514' relation: part_of_dissertation status: public - id: '21982' relation: part_of_dissertation status: public researchdata_availability: yes status: public supervisor: - first_name: Scott R full_name: Waitukaitis, Scott R id: 3A1FFC16-F248-11E8-B48F-1D18A9856A87 last_name: Waitukaitis orcid: 0000-0002-2299-3176 supplementarymaterial: yes title: The morphology underneath a levitated hydrogel sphere 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: 8b945eb4-e2f2-11eb-945a-df72226e66a9 year: '2026' ... --- OA_place: publisher _id: '22984' acknowledged_ssus: - _id: Bio - _id: LifeSc - _id: MassSpec alternative_title: - ISTA Thesis article_processing_charge: No author: - first_name: Anastasiia full_name: Teplova, Anastasiia id: e3736151-106c-11ec-b916-c2558e2762c6 last_name: Teplova citation: ama: 'Teplova A. Chasing the elusive: Investigating nucleotide cyclase activity in gibberellin and strigolactone signalling; Cellular mechanisms of gravity sensing and response in roots. 2026. doi:10.15479/AT-ISTA-22984' apa: 'Teplova, A. (2026). Chasing the elusive: Investigating nucleotide cyclase activity in gibberellin and strigolactone signalling; Cellular mechanisms of gravity sensing and response in roots. Institute of Science and Technology Austria. https://doi.org/10.15479/AT-ISTA-22984' chicago: 'Teplova, Anastasiia. “Chasing the Elusive: Investigating Nucleotide Cyclase Activity in Gibberellin and Strigolactone Signalling; Cellular Mechanisms of Gravity Sensing and Response in Roots.” Institute of Science and Technology Austria, 2026. https://doi.org/10.15479/AT-ISTA-22984.' ieee: 'A. Teplova, “Chasing the elusive: Investigating nucleotide cyclase activity in gibberellin and strigolactone signalling; Cellular mechanisms of gravity sensing and response in roots,” Institute of Science and Technology Austria, 2026.' ista: 'Teplova A. 2026. Chasing the elusive: Investigating nucleotide cyclase activity in gibberellin and strigolactone signalling; Cellular mechanisms of gravity sensing and response in roots. Institute of Science and Technology Austria.' mla: 'Teplova, Anastasiia. Chasing the Elusive: Investigating Nucleotide Cyclase Activity in Gibberellin and Strigolactone Signalling; Cellular Mechanisms of Gravity Sensing and Response in Roots. Institute of Science and Technology Austria, 2026, doi:10.15479/AT-ISTA-22984.' short: 'A. Teplova, Chasing the Elusive: Investigating Nucleotide Cyclase Activity in Gibberellin and Strigolactone Signalling; Cellular Mechanisms of Gravity Sensing and Response in Roots, Institute of Science and Technology Austria, 2026.' corr_author: '1' date_created: 2026-09-23T15:29:42Z date_published: 2026-09-23T00:00:00Z date_updated: 2026-10-02T07:48:48Z day: '23' ddc: - '570' degree_awarded: PhD department: - _id: GradSch - _id: JiFr doi: 10.15479/AT-ISTA-22984 doi_confirm: '1' file: - access_level: closed checksum: ae6e37780e4a8d07cfabf0a899c6c6bf content_type: application/vnd.openxmlformats-officedocument.wordprocessingml.document creator: ateplova date_created: 2026-09-25T09:19:25Z date_updated: 2026-09-25T09:19:25Z file_id: '22996' file_name: 2026-Teplova-Anastasia-Thesis-final.docx file_size: 106736394 relation: source_file - access_level: closed checksum: 305099d360d30bd596af946171d19c3b content_type: application/pdf creator: ateplova date_created: 2026-09-25T09:25:56Z date_updated: 2026-09-25T09:25:56Z embargo: 2027-09-30 embargo_to: open_access file_id: '22997' file_name: 2026-Teplova-Anastasia-Thesis-final-pdfA.pdf file_size: 39343452 relation: main_file file_date_updated: 2026-09-25T09:25:56Z fulldoi: https://doi.org/10.15479/AT-ISTA-22984 has_accepted_license: '1' language: - iso: eng month: '09' oa_version: Published Version page: '190' publication_identifier: isbn: - 978-3-99078-093-0 issn: - '2663-337X ' publication_status: published publisher: Institute of Science and Technology Austria related_material: record: - id: '15257' 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: 'Chasing the elusive: Investigating nucleotide cyclase activity in gibberellin and strigolactone signalling; Cellular mechanisms of gravity sensing and response in roots' type: dissertation user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9 year: '2026' ...