--- OA_place: repository OA_type: green _id: '21858' abstract: - lang: eng text: "The recent surge in high-quality open-source Generative AI text models (colloquially: LLMs), as well as efficient finetuning techniques, have opened the possibility of creating high-quality personalized models that generate text attuned to a specific individual’s needs and are capable of credibly imitating their writing style by refining an open-source model with that person’s own data. The technology to create such models is accessible to private individuals, and training and running such models can be done cheaply on consumer-grade hardware. While these advancements are a huge gain for usability and privacy, this position paper argues that the practical feasibility of impersonating specific individuals also introduces novel safety risks. For instance, this technology enables the creation of phishing emails\r\nor fraudulent social media accounts, based on small amounts of publicly available text, or by the individuals themselves to escape AI text detection. We further argue that these risks are complementary to—and distinct from—the much-discussed risks of other impersonation attacks such as image, voice, or video deepfakes, and are not adequately addressed by the larger research community, or the current generation of open- and closed-source models." acknowledgement: "This research was supported by the Scientific Service Units (SSU) of IST Austria through resources\r\nprovided by Scientific Computing (SciComp). EI was supported in part by the FWF DK VGSCO,\r\ngrant agreement number W1260-N35. AJ was supported in part by ERC Proof-of-Concept Grant\r\nFastML, grant agreement 101158077." article_processing_charge: No arxiv: 1 author: - first_name: Eugenia B full_name: Iofinova, Eugenia B id: f9a17499-f6e0-11ea-865d-fdf9a3f77117 last_name: Iofinova orcid: 0000-0002-7778-3221 - first_name: Andrej full_name: Jovanovic, Andrej last_name: Jovanovic - first_name: Dan-Adrian full_name: Alistarh, Dan-Adrian id: 4A899BFC-F248-11E8-B48F-1D18A9856A87 last_name: Alistarh orcid: 0000-0003-3650-940X citation: ama: 'Iofinova EB, Jovanovic A, Alistarh D-A. Position: It’s time to act on the risk of efficient personalized text generation. arXiv. doi:10.48550/arXiv.2502.06560' apa: 'Iofinova, E. B., Jovanovic, A., & Alistarh, D.-A. (n.d.). Position: It’s time to act on the risk of efficient personalized text generation. arXiv. https://doi.org/10.48550/arXiv.2502.06560' chicago: 'Iofinova, Eugenia B, Andrej Jovanovic, and Dan-Adrian Alistarh. “Position: It’s Time to Act on the Risk of Efficient Personalized Text Generation.” ArXiv, n.d. https://doi.org/10.48550/arXiv.2502.06560.' ieee: 'E. B. Iofinova, A. Jovanovic, and D.-A. Alistarh, “Position: It’s time to act on the risk of efficient personalized text generation,” arXiv. .' ista: 'Iofinova EB, Jovanovic A, Alistarh D-A. Position: It’s time to act on the risk of efficient personalized text generation. arXiv, 10.48550/arXiv.2502.06560.' mla: 'Iofinova, Eugenia B., et al. “Position: It’s Time to Act on the Risk of Efficient Personalized Text Generation.” ArXiv, doi:10.48550/arXiv.2502.06560.' short: E.B. Iofinova, A. Jovanovic, D.-A. Alistarh, ArXiv (n.d.). corr_author: '1' date_created: 2026-05-11T08:55:23Z date_published: 2025-06-02T00:00:00Z date_updated: 2026-07-27T12:50:03Z day: '02' department: - _id: GradSch - _id: DaAl doi: 10.48550/arXiv.2502.06560 external_id: arxiv: - '2502.06560' fulldoi: https://doi.org/10.48550/arXiv.2502.06560 language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.48550/arXiv.2502.06560 month: '06' oa: 1 oa_version: Preprint project: - _id: 8e35c14b-16d5-11f0-9cad-a3fc35339161 grant_number: '101158077' name: 'FastML: Efficient and Cost-Effective Distributed Machine Learning' - _id: 9B9290DE-BA93-11EA-9121-9846C619BF3A grant_number: W1260-N35 name: Vienna Graduate School on Computational Optimization publication: arXiv publication_status: draft related_material: record: - id: '21854' relation: dissertation_contains status: public status: public title: 'Position: It''s time to act on the risk of efficient personalized text generation' type: preprint user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9 year: '2025' ... --- OA_place: repository OA_type: green _id: '21144' abstract: - lang: eng text: 'This paper deals with the algorithmic aspects of solving feasibility problems of semidefinite programming (SDP), aka linear matrix inequalities (LMIs). Since in some SDP instances all feasible solutions have irrational entries, numerical solvers that work with rational numbers can only find an approximate solution. We study the following question: Is it possible to certify feasibility of a given SDP using an approximate solution that is sufficiently close to some exact solution? Existing approaches make the assumption that there exist rational feasible solutions (and use techniques such as rounding and lattice reduction algorithms). We propose an alternative approach that does not need this assumption. More specifically, we show how to construct a system of polynomial equations whose set of real solutions is guaranteed to have an isolated correct solution (assuming that the target exact solution is maximum-rank). This allows, in particular, for us to use algorithms from real algebraic geometry for solving systems of polynomial equations, yielding a hybrid (or symbolic-numerical) method for SDPs. We experimentally compare it with a pure symbolic method in [D. Henrion, S. Naldi, and M. Safey El Din, SIAM J. Optim., 26 (2016), pp. 2512–2539]; the hybrid method was able to certify feasibility of many SDP instances on which the aforementioned paper failed. Our approach may have further applications, such as refining an approximate solution using methods of numerical algebraic geometry for systems of polynomial equations.' article_processing_charge: No article_type: original arxiv: 1 author: - first_name: Vladimir full_name: Kolmogorov, Vladimir id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87 last_name: Kolmogorov - first_name: Simone full_name: Naldi, Simone last_name: Naldi - first_name: Jeferson full_name: Zapata, Jeferson id: 00223538-AF8F-11E9-A4C7-F729E6697425 last_name: Zapata citation: ama: Kolmogorov V, Naldi S, Zapata J. Certifying solutions of degenerate semidefinite programs. SIAM Journal on Optimization. 2025;35(3):1630-1654. doi:10.1137/24m1664691 apa: Kolmogorov, V., Naldi, S., & Zapata, J. (2025). Certifying solutions of degenerate semidefinite programs. SIAM Journal on Optimization. Society for Industrial and Applied Mathematics. https://doi.org/10.1137/24m1664691 chicago: Kolmogorov, Vladimir, Simone Naldi, and Jeferson Zapata. “Certifying Solutions of Degenerate Semidefinite Programs.” SIAM Journal on Optimization. Society for Industrial and Applied Mathematics, 2025. https://doi.org/10.1137/24m1664691. ieee: V. Kolmogorov, S. Naldi, and J. Zapata, “Certifying solutions of degenerate semidefinite programs,” SIAM Journal on Optimization, vol. 35, no. 3. Society for Industrial and Applied Mathematics, pp. 1630–1654, 2025. ista: Kolmogorov V, Naldi S, Zapata J. 2025. Certifying solutions of degenerate semidefinite programs. SIAM Journal on Optimization. 35(3), 1630–1654. mla: Kolmogorov, Vladimir, et al. “Certifying Solutions of Degenerate Semidefinite Programs.” SIAM Journal on Optimization, vol. 35, no. 3, Society for Industrial and Applied Mathematics, 2025, pp. 1630–54, doi:10.1137/24m1664691. short: V. Kolmogorov, S. Naldi, J. Zapata, SIAM Journal on Optimization 35 (2025) 1630–1654. date_created: 2026-02-05T13:33:05Z date_published: 2025-09-01T00:00:00Z date_updated: 2026-07-27T14:30:41Z day: '01' department: - _id: VlKo - _id: GradSch doi: 10.1137/24m1664691 external_id: arxiv: - '2405.13625' fulldoi: https://doi.org/10.1137/24m1664691 intvolume: ' 35' issue: '3' language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.48550/arXiv.2405.13625 month: '09' oa: 1 oa_version: Preprint page: 1630-1654 publication: SIAM Journal on Optimization publication_identifier: eissn: - 1095-7189 issn: - 1052-6234 publication_status: published publisher: Society for Industrial and Applied Mathematics quality_controlled: '1' related_material: record: - id: '21957' relation: dissertation_contains status: public status: public title: Certifying solutions of degenerate semidefinite programs type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 35 year: '2025' ... --- OA_place: publisher _id: '20735' abstract: - lang: eng text: "Left–right alternation is a defining feature of spinal locomotor circuits, yet the level of neuronal\r\ndetail required to generate and maintain this pattern remains unclear. This thesis investigates how\r\nmodels spanning multiple levels of abstraction—from biophysically detailed Hodgkin–Huxley (HH)\r\nneurons to adaptive integrate–and–fire (I&F) formulations and synfire-chain modules—can account\r\nfor the generation of fictive swimming in the spinal cord of the Xenopus laevis tadpole. The guiding\r\nhypothesis is that a small set of neuronal mechanisms is sufficient to reproduce the essential features\r\nof rhythmic alternation, and that moving between modeling scales helps distinguish core principles\r\nfrom biological detail.\r\nA minimal bilateral HH network comprising only four canonical neuron classes—excitatory\r\ndescending interneurons (dINs), inhibitory commissural interneurons (cINs), ipsilateral inhibitory\r\ninterneurons (aINs) and motoneurons—served as a biophysical proof of concept. Tuned to reproduce\r\nexperimentally observed firing modes, the model demonstrated that rebound-prone dIN excitability,\r\ncontralateral inhibition and modest electrical coupling are sufficient to generate stable alternating\r\nactivity, even in very small networks. These results motivated the transition to simpler models\r\ncapable of efficient analysis and scaling.\r\nAdaptive exponential I&F (AdEx) neurons were calibrated to physiological recordings using\r\nsimulation-based inference, yielding tonic and phasic/rebound templates that preserved the key\r\ndynamical signatures of the HH model. Phase-plane analysis clarified the mechanisms underlying\r\nsingle-spike responses and rebound firing in dINs. At network level, the I&F models robustly\r\nreproduced left–right alternation, while highlighting constraints on synaptic kinetics and adaptation\r\nneeded to avoid multi-spike responses.\r\nFinally, a synfire-chain framework provided a complementary, timing-centric perspective, demonstrating how precise spike synchrony, synaptic delays and minimal inhibitory coupling can generate\r\nalternating left–right sequences in a feedforward setting. Together, these approaches converge on a\r\ncommon conclusion: rebound-prone ipsilateral excitation combined with precisely timed contralateral inhibition constitutes a sufficient substrate for alternating spinal rhythms.\r\nBy integrating bottom-up and top-down modeling strategies, this thesis provides a unified, extensible framework for studying spinal pattern generation. The results show that essential locomotor\r\ndynamics can be captured across multiple abstraction levels, offering both mechanistic insight and\r\npractical tools for future data-driven investigations of spinal circuit development, robustness and\r\nmodulation." alternative_title: - ISTA Master's Thesis article_processing_charge: No author: - first_name: Alexia C full_name: Wilson, Alexia C id: 5230e794-15b2-11ec-abd3-e2d5335ebd1d last_name: Wilson orcid: 0000-0001-6191-1367 citation: ama: 'Wilson AC. Modelling the spinal cord of a tadpole: Exploring different ways to model the spinal cord in the Xenopus frog. 2025. doi:10.15479/AT-ISTA-20735' apa: 'Wilson, A. C. (2025). Modelling the spinal cord of a tadpole: Exploring different ways to model the spinal cord in the Xenopus frog. Institute of Science and Technology Austria. https://doi.org/10.15479/AT-ISTA-20735' chicago: 'Wilson, Alexia C. “Modelling the Spinal Cord of a Tadpole: Exploring Different Ways to Model the Spinal Cord in the Xenopus Frog.” Institute of Science and Technology Austria, 2025. https://doi.org/10.15479/AT-ISTA-20735.' ieee: 'A. C. Wilson, “Modelling the spinal cord of a tadpole: Exploring different ways to model the spinal cord in the Xenopus frog,” Institute of Science and Technology Austria, 2025.' ista: 'Wilson AC. 2025. Modelling the spinal cord of a tadpole: Exploring different ways to model the spinal cord in the Xenopus frog. Institute of Science and Technology Austria.' mla: 'Wilson, Alexia C. Modelling the Spinal Cord of a Tadpole: Exploring Different Ways to Model the Spinal Cord in the Xenopus Frog. Institute of Science and Technology Austria, 2025, doi:10.15479/AT-ISTA-20735.' short: 'A.C. Wilson, Modelling the Spinal Cord of a Tadpole: Exploring Different Ways to Model the Spinal Cord in the Xenopus Frog, Institute of Science and Technology Austria, 2025.' corr_author: '1' date_created: 2025-12-08T09:49:41Z date_published: 2025-12-09T00:00:00Z date_updated: 2026-07-29T12:55:12Z day: '09' ddc: - '570' - '596' - '005' degree_awarded: MS department: - _id: GradSch - _id: TiVo - _id: LoSw doi: 10.15479/AT-ISTA-20735 doi_confirm: '1' file: - access_level: closed checksum: 9e3b6b73f8cbec2c3687d17fe8e30410 content_type: application/zip creator: awilson date_created: 2026-01-01T17:26:30Z date_updated: 2026-01-02T13:05:07Z file_id: '20919' file_name: tadpoleAdEx.zip file_size: 566072368 relation: source_file - access_level: open_access checksum: 13f4c0d33923e9d5c9d56731345cf21d content_type: application/pdf creator: awilson date_created: 2026-01-04T12:58:49Z date_updated: 2026-01-04T12:58:49Z file_id: '20923' file_name: Masters_Thesis_Alexia_Wilson_FINAL_pdfA.pdf file_size: 7170097 relation: main_file success: 1 file_date_updated: 2026-01-04T12:58:49Z fulldoi: https://doi.org/10.15479/AT-ISTA-20735 has_accepted_license: '1' language: - iso: eng month: '12' oa: 1 oa_version: Published Version page: '110' publication_identifier: issn: - 2791-4585 publication_status: published publisher: Institute of Science and Technology Austria related_material: record: - id: '13097' relation: part_of_dissertation status: public status: public supervisor: - first_name: Tim P full_name: Vogels, Tim P id: CB6FF8D2-008F-11EA-8E08-2637E6697425 last_name: Vogels orcid: 0000-0003-3295-6181 - 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 title: 'Modelling the spinal cord of a tadpole: Exploring different ways to model the spinal cord in the Xenopus frog' type: dissertation user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9 year: '2025' ... --- OA_place: repository OA_type: green _id: '21398' abstract: - lang: eng text: Seymour's decomposition theorem is a hallmark result in matroid theory presenting a structural characterization of the class of regular matroids. Formalization of matroid theory faces many challenges, most importantly that only a limited number of notions and results have been implemented so far. In this work, we formalize the proof of the forward (composition) direction of Seymour's theorem for regular matroids. To this end, we develop a library in Lean 4 that implements definitions and results about totally unimodular matrices, vector matroids, their standard representations, regular matroids, and 1-, 2-, and 3-sums of matrices and binary matroids given by their standard representations. Using this framework, we formally state Seymour's decomposition theorem and implement a formally verified proof of the composition direction in the setting where the matroids have finite rank and may have infinite ground sets. acknowledgement: "We would like to dedicate the paper to the memory of Klaus Truemper, whose monograph Matroid Decomposition [12]\r\nlaid the foundation for our entire work." article_number: '2509.20539' article_processing_charge: No arxiv: 1 author: - first_name: Martin full_name: Dvorak, Martin id: 40ED02A8-C8B4-11E9-A9C0-453BE6697425 last_name: Dvorak orcid: 0000-0001-5293-214X - first_name: Tristan full_name: Figueroa-Reid, Tristan last_name: Figueroa-Reid - first_name: Rida full_name: Hamadani, Rida last_name: Hamadani - first_name: Byung-Hak full_name: Hwang, Byung-Hak last_name: Hwang - first_name: Evgenia full_name: Karunus, Evgenia last_name: Karunus - first_name: Vladimir full_name: Kolmogorov, Vladimir id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87 last_name: Kolmogorov - first_name: Alexander full_name: Meiburg, Alexander last_name: Meiburg - first_name: Alexander full_name: Nelson, Alexander last_name: Nelson - first_name: Peter full_name: Nelson, Peter last_name: Nelson - first_name: Mark full_name: Sandey, Mark last_name: Sandey - first_name: Ivan full_name: Sergeev, Ivan id: ca3c9187-9a72-11ee-a009-8af825d896b0 last_name: Sergeev orcid: 0009-0004-9145-8785 citation: ama: Dvorak M, Figueroa-Reid T, Hamadani R, et al. Composition direction of Seymour’s theorem for regular matroids — Formally verified. arXiv. doi:10.48550/arXiv.2509.20539 apa: Dvorak, M., Figueroa-Reid, T., Hamadani, R., Hwang, B.-H., Karunus, E., Kolmogorov, V., … Sergeev, I. (n.d.). Composition direction of Seymour’s theorem for regular matroids — Formally verified. arXiv. https://doi.org/10.48550/arXiv.2509.20539 chicago: Dvorak, Martin, Tristan Figueroa-Reid, Rida Hamadani, Byung-Hak Hwang, Evgenia Karunus, Vladimir Kolmogorov, Alexander Meiburg, et al. “Composition Direction of Seymour’s Theorem for Regular Matroids — Formally Verified.” ArXiv, n.d. https://doi.org/10.48550/arXiv.2509.20539. ieee: M. Dvorak et al., “Composition direction of Seymour’s theorem for regular matroids — Formally verified,” arXiv. . ista: Dvorak M, Figueroa-Reid T, Hamadani R, Hwang B-H, Karunus E, Kolmogorov V, Meiburg A, Nelson A, Nelson P, Sandey M, Sergeev I. Composition direction of Seymour’s theorem for regular matroids — Formally verified. arXiv, 2509.20539. mla: Dvorak, Martin, et al. “Composition Direction of Seymour’s Theorem for Regular Matroids — Formally Verified.” ArXiv, 2509.20539, doi:10.48550/arXiv.2509.20539. short: M. Dvorak, T. Figueroa-Reid, R. Hamadani, B.-H. Hwang, E. Karunus, V. Kolmogorov, A. Meiburg, A. Nelson, P. Nelson, M. Sandey, I. Sergeev, ArXiv (n.d.). corr_author: '1' das_tickbox: '1' date_created: 2026-03-04T11:56:29Z date_published: 2025-09-23T00:00:00Z date_updated: 2026-07-29T12:56:51Z day: '23' department: - _id: GradSch - _id: VlKo doi: 10.48550/arXiv.2509.20539 external_id: arxiv: - '2509.20539' fulldoi: https://doi.org/10.48550/arXiv.2509.20539 language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.48550/arXiv.2509.20539 month: '09' oa: 1 oa_version: Preprint publication: arXiv publication_status: draft related_material: record: - id: '21393' relation: dissertation_contains status: public status: public title: Composition direction of Seymour's theorem for regular matroids — Formally verified type: preprint user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2025' ... --- OA_place: publisher _id: '20371' abstract: - lang: eng text: "Quantum mechanics reveals a world that defies classical determinism, where uncertainty, superposition, and fluctuations are fundamental aspects. Engineering devices that harness these quantum features requires not only precision, but also a deep understanding of how they interact with their surrounding environment. Superconducting circuits, which exploit\r\nmacroscopic quantum coherence in low-loss superconducting materials, provide a scalable platform for implementing such systems. Among the critical elements in these circuits, superinductors—high-impedance, dissipation-free inductive components—play a central role by suppressing charge fluctuations. They allow quantum states to be delocalized in phase space, protect qubits from environmental noise, and facilitate access to phenomena such as dual Josephson physics and ultra-strong coupling regimes. \r\nThis thesis explores two complementary implementations of high-impedance circuits: geometric superinductors, demonstrating that high impedance can be achieved beyond kinetic inductance,\r\nand Josephson junction chains, used to investigate both microwave mode properties and DC transport across the superconductor-to-insulator transition. \r\nPart I addresses geometric superinductors. Contrary to the common belief that high-impedance superconducting circuits require kinetic inductance, we demonstrate that purely geometric designs can achieve characteristic impedance exceeding the resistance quantum. By exploiting mutual coupling between adjacent turns, coil-based inductors achieve enhanced self-inductance, creating a reliable platform for qubits and resonators. Modeling, simulation, fabrication, and\r\ncharacterization confirm that these elements behave as superinductor. With low loss, high linearity, and minimal stray capacitance, these elements are reproducible, free of uncontrolled tunneling events, and capable of strong magnetic coupling. This establishes geometric superinductors as robust, single-wave-function superconducting devices suitable for hardware protected qubits and hybrid systems.\r\nPart II presents classical numerical simulations of a Quantum Phase Slip circuit to study dual Shapiro steps. The circuit consists of an ideal Quantum Phase Slip element embedded in a resistive-inductive environment with a parasitic capacitance.\r\nPart III extends the investigation of high characteristic-impedance circuit elements to one-dimensional Josephson junction chains, which act as a quantum simulator for many-body physics and the superconductor–insulator transition. Different devices are realized on both sides of the DC phase transition, showing either a supercurrent branch or Coulomb blockade at zero bias. The effect of the crossover on microwave modes, however, remains insufficiently investigated. Studying these modes provides insight into the interplay between disorder and phase-slip events. Small differences in circuit component sizes determine which side of the transition a device falls on, making these results relevant not only for fundamental understanding but also for the design of quantum devices, emphasizing the crucial role of the\r\nelectromagnetic environment in stabilizing and controlling fragile quantum states. \r\nTogether, these results illustrate how carefully engineered high characteristic-impedance elements provide a link between macroscopic circuits and the inherently uncertain quantum world, enabling experiments that probe, control, and ultimately exploit quantum fluctuations for applications in quantum information, metrology, solid state physics and beyond.\r\n\r\n" acknowledged_ssus: - _id: NanoFab - _id: M-Shop acknowledgement: "I also gratefully acknowledge the generous support of the NOMIS Foundation Project \"Protected\r\nStates of Quantum Matter\" and the grant from the Beyond-C consortium. Their funding\r\nmade this research possible and gave me the freedom to ask ambitious questions, and try to\r\nanswer them.\r\n" alternative_title: - ISTA Thesis article_processing_charge: No author: - first_name: Andrea full_name: Trioni, Andrea id: 42F71B44-F248-11E8-B48F-1D18A9856A87 last_name: Trioni citation: ama: 'Trioni A. High-impedance quantum circuits for mesoscopic physics: Geometric superinductors and insulating Josephson Chains. 2025. doi:10.15479/AT-ISTA-20371' apa: 'Trioni, A. (2025). High-impedance quantum circuits for mesoscopic physics: Geometric superinductors and insulating Josephson Chains. Institute of Science and Technology Austria. https://doi.org/10.15479/AT-ISTA-20371' chicago: 'Trioni, Andrea. “High-Impedance Quantum Circuits for Mesoscopic Physics: Geometric Superinductors and Insulating Josephson Chains.” Institute of Science and Technology Austria, 2025. https://doi.org/10.15479/AT-ISTA-20371.' ieee: 'A. Trioni, “High-impedance quantum circuits for mesoscopic physics: Geometric superinductors and insulating Josephson Chains,” Institute of Science and Technology Austria, 2025.' ista: 'Trioni A. 2025. High-impedance quantum circuits for mesoscopic physics: Geometric superinductors and insulating Josephson Chains. Institute of Science and Technology Austria.' mla: 'Trioni, Andrea. High-Impedance Quantum Circuits for Mesoscopic Physics: Geometric Superinductors and Insulating Josephson Chains. Institute of Science and Technology Austria, 2025, doi:10.15479/AT-ISTA-20371.' short: 'A. Trioni, High-Impedance Quantum Circuits for Mesoscopic Physics: Geometric Superinductors and Insulating Josephson Chains, Institute of Science and Technology Austria, 2025.' corr_author: '1' date_created: 2025-09-23T09:57:57Z date_published: 2025-09-23T00:00:00Z date_updated: 2026-07-29T13:12:10Z day: '23' ddc: - '539' degree_awarded: PhD department: - _id: GradSch - _id: JoFi doi: 10.15479/AT-ISTA-20371 doi_confirm: '1' ec_funded: 1 file: - access_level: open_access checksum: 6fb925648dfa5f4384814c552ee2f099 content_type: application/pdf creator: atrioni date_created: 2025-09-25T07:15:05Z date_updated: 2025-09-25T14:25:31Z file_id: '20392' file_name: 2025_Trioni_Andrea_Thesis.pdf file_size: 22351676 relation: main_file - access_level: closed checksum: 619dc614bdfbf3999b76ac8890b2cebd content_type: application/x-zip-compressed creator: atrioni date_created: 2025-09-25T14:45:43Z date_updated: 2025-09-26T07:20:48Z file_id: '20396' file_name: 2025_Trioni_Andrea_Thesis.zip file_size: 60079009 relation: source_file file_date_updated: 2025-09-26T07:20:48Z fulldoi: https://doi.org/10.15479/AT-ISTA-20371 has_accepted_license: '1' language: - iso: eng month: '09' oa: 1 oa_version: Published Version page: '202' project: - _id: eb9b30ac-77a9-11ec-83b8-871f581d53d2 name: Protected states of quantum matter - _id: bdb108fd-d553-11ed-ba76-83dc74a9864f grant_number: F07105 name: QUANTUM INFORMATION SYSTEMS BEYOND CLASSICAL CAPABILITIES / P5- Integration of Superconducting Quantum Circuits - _id: 2564DBCA-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '665385' name: International IST Doctoral Program publication_identifier: isbn: - 978-3-99078-067-1 issn: - 2663-337X publication_status: published publisher: Institute of Science and Technology Austria related_material: record: - id: '8755' relation: part_of_dissertation status: public status: public supervisor: - first_name: Johannes M full_name: Fink, Johannes M id: 4B591CBA-F248-11E8-B48F-1D18A9856A87 last_name: Fink orcid: 0000-0001-8112-028X title: 'High-impedance quantum circuits for mesoscopic physics: Geometric superinductors and insulating Josephson Chains' type: dissertation user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9 year: '2025' ... --- _id: '20641' abstract: - lang: eng text: 'Protein conformational energy landscapes are shaped not only by intramolecular interactions but also by their environment. In protein crystals and protein-protein complexes, intermolecular contacts alter this energy landscape, but the exact nature of this alteration is difficult to decipher. Understanding how the crystal lattice affects protein dynamics is crucial for crystallography-based studies of motion, yet its influence on collective motions remains unclear. Aromatic ring flips in the hydrophobic core represent sensitive probes of such dynamics. Here, we compare the kinetics of aromatic ring flips in the protein GB1 in crystals, in complex with its binding partner IgG, and in solution, combining advanced isotope labeling with quantitative NMR methods. We show that rings in the core flip nearly a thousand times less frequently in crystals than in solution. Enhanced-sampling molecular dynamics simulations, based on a new crystal structure, reproduce these elevated barriers and reveal how the crystal restrains motions. ' acknowledged_ssus: - _id: NMR - _id: LifeSc acknowledgement: "We thank Nikolai R. Skrynnikov and Olga O. Lebedenko (St. Petersburg) for insightful discussions and for performing exploratory MD simulations. We are grateful to Tobias Schubeis (Lyon) for advice with GB1 crystallization, and Rebecca Schmid for initial crystallization trials.\r\nWe thank Sebastian Falkner for assistance with constructing the structural model of the IgG:GB1 complex.\r\nThis research was supported by the Scientific Service Units (SSU) of Institute of Science and Technology Austria (ISTA) through resources provided by the Nuclear Magnetic Resonance and the Lab Support Facilities. We thank Petra Rovó and Margarita Valhondo Falcón for excellent support of the NMR facility.\r\nLea M. Becker is recipient of a DOC fellowship of the Austrian Academy of Sciences at the Institute of Science and Technology Austria (grant no. PR10660EAW01). Christophe Chipot acknowledges the European Research Council (grant project 101097272 ``MilliInMicro'') and the Métropole du Grand Nancy (grant project ``ARC''). BM07-FIP2 is supported by the French ANR PIA3 (France 2030) EquipEx+ project MAGNIFIX under grant agreement ANR-21-ESRE-0011." article_processing_charge: No author: - first_name: Lea Marie full_name: Becker, Lea Marie id: 36336939-eb97-11eb-a6c2-c83f1214ca79 last_name: Becker orcid: 0000-0002-6401-5151 - first_name: Paul full_name: Schanda, Paul id: 7B541462-FAF6-11E9-A490-E8DFE5697425 last_name: Schanda orcid: 0000-0002-9350-7606 citation: ama: Becker LM, Schanda P. Data for “Aromatic Ring Flips Reveal Reshaping of Protein Dynamics in Crystals and Complexes.” 2025. doi:10.15479/AT-ISTA-20641 apa: Becker, L. M., & Schanda, P. (2025). Data for “Aromatic Ring Flips Reveal Reshaping of Protein Dynamics in Crystals and Complexes.” Institute of Science and Technology Austria. https://doi.org/10.15479/AT-ISTA-20641 chicago: Becker, Lea Marie, and Paul Schanda. “Data for ‘Aromatic Ring Flips Reveal Reshaping of Protein Dynamics in Crystals and Complexes.’” Institute of Science and Technology Austria, 2025. https://doi.org/10.15479/AT-ISTA-20641. ieee: L. M. Becker and P. Schanda, “Data for ‘Aromatic Ring Flips Reveal Reshaping of Protein Dynamics in Crystals and Complexes.’” Institute of Science and Technology Austria, 2025. ista: Becker LM, Schanda P. 2025. Data for ‘Aromatic Ring Flips Reveal Reshaping of Protein Dynamics in Crystals and Complexes’, Institute of Science and Technology Austria, 10.15479/AT-ISTA-20641. mla: Becker, Lea Marie, and Paul Schanda. Data for “Aromatic Ring Flips Reveal Reshaping of Protein Dynamics in Crystals and Complexes.” Institute of Science and Technology Austria, 2025, doi:10.15479/AT-ISTA-20641. short: L.M. Becker, P. Schanda, (2025). contributor: - contributor_type: researcher first_name: 'Haohao ' last_name: Fu - contributor_type: researcher first_name: Benjamin id: 71cda2f3-e604-11ee-a1df-da10587eda3f last_name: Tatman - contributor_type: researcher first_name: Matthias last_name: Dreydoppel - contributor_type: researcher first_name: Anna id: 9fb2a840-89e1-11ee-a8b7-cc5c7ba62471 last_name: Kapitonova - contributor_type: researcher first_name: Daniel id: 302BADF6-85FC-11EA-9E3B-B9493DDC885E last_name: Balazs orcid: 0000-0001-7597-043X - contributor_type: researcher first_name: Ulrich last_name: Weininger - contributor_type: researcher first_name: Sylvain last_name: Engilberge - contributor_type: researcher first_name: Christophe last_name: Chipot corr_author: '1' date_created: 2025-11-13T09:29:58Z date_published: 2025-11-18T00:00:00Z date_updated: 2026-08-04T09:32:44Z day: '18' ddc: - '572' department: - _id: GradSch - _id: PaSc doi: 10.15479/AT-ISTA-20641 file: - access_level: open_access checksum: a73a0550c644957e7f62241e239d3a1d content_type: application/zip creator: lbecker date_created: 2025-11-13T09:38:35Z date_updated: 2026-02-17T10:16:57Z file_id: '20643' file_name: Research_Data.zip file_size: 1806589513 relation: main_file - access_level: open_access checksum: 7176b257f753c213a0460ee06f802363 content_type: application/pdf creator: lbecker date_created: 2025-11-17T11:54:17Z date_updated: 2026-02-17T10:16:57Z file_id: '20652' file_name: README.pdf file_size: 191376 relation: table_of_contents file_date_updated: 2026-02-17T10:16:57Z fulldoi: https://doi.org/10.15479/AT-ISTA-20641 has_accepted_license: '1' license: https://creativecommons.org/licenses/by-nc/4.0/ month: '11' oa: 1 oa_version: Published Version project: - _id: 7be609c4-9f16-11ee-852c-85015ce2b9b0 grant_number: '26777' name: Exploring protein dynamics by solid-state MAS NMR through specific labeling approaches publisher: Institute of Science and Technology Austria related_material: record: - id: '21145' relation: later_version status: public - id: '22105' relation: used_in_publication status: public status: public title: Data for "Aromatic Ring Flips Reveal Reshaping of Protein Dynamics in Crystals and Complexes" 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: '2025' ... --- OA_place: repository OA_type: green _id: '20926' abstract: - lang: eng text: Most current machine learning interatomic potentials (MLIPs) rely on short-range approximations, without explicit treatment of long-range electrostatics. To address this, we recently developed the Latent Ewald Summation (LES) method, which infers electrostatic interactions, polarization, and Born effective charges (BECs), just by learning from energy and force training data. Here, we present LES as a standalone library, compatible with any short-range MLIP, and demonstrate its integration with methods such as MACE, NequIP, Allegro, CACE, CHGNet, and UMA. We benchmark LES-enhanced models on distinct systems, including bulk water, polar dipeptides, and gold dimer adsorption on defective substrates, and show that LES not only captures correct electrostatics but also improves accuracy. Additionally, we scale LES to large and chemically diverse data by training MACELES-OFF on the SPICE set containing molecules and clusters, making a universal MLIP with electrostatics for organic systems, including biomolecules. MACELES-OFF is more accurate than its short-range counterpart (MACE-OFF) trained on the same data set, predicts dipoles and BECs reliably, and has better descriptions of bulk liquids. By enabling efficient long-range electrostatics without directly training on electrical properties, LES paves the way for electrostatic foundation MLIPs. acknowledgement: Research reported in this publication was supported by the National Institute Of General Medical Sciences of the National Institutes of Health under Award Number R35GM159986. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. D.K. and B.C. acknowledge funding from Toyota Research Institute Synthesis Advanced Research Challenge. T.J.I., D.S.K. and P.Z. acknowledge funding from BIDMaP Postdoctoral Fellowship. T.J.I. used resources of the National Energy Research Scientific Computing Center (NERSC), a Department of Energy Office of Science User Facility using NERSC award DOEERCAP0031751 ′GenAI@NERSC’. The authors thank Bowen Deng for valuable discussions on MatGL implementation, and thank Gabor Csanyi for stimulating discussions. article_processing_charge: No article_type: original arxiv: 1 author: - first_name: Dongjin full_name: Kim, Dongjin last_name: Kim - first_name: Xiaoyu full_name: Wang, Xiaoyu id: 8dff9c62-32b0-11ee-9fa8-fc73025e10f3 last_name: Wang - first_name: Santiago full_name: Vargas, Santiago last_name: Vargas - first_name: Peichen full_name: Zhong, Peichen last_name: Zhong - first_name: Daniel S. full_name: King, Daniel S. last_name: King - first_name: Theo Jaffrelot full_name: Inizan, Theo Jaffrelot last_name: Inizan - first_name: Bingqing full_name: Cheng, Bingqing id: cbe3cda4-d82c-11eb-8dc7-8ff94289fcc9 last_name: Cheng orcid: 0000-0002-3584-9632 citation: ama: Kim D, Wang X, Vargas S, et al. A universal augmentation framework for long-range electrostatics in machine learning interatomic potentials. Journal of Chemical Theory and Computation. 2025;21(24):12709-12724. doi:10.1021/acs.jctc.5c01400 apa: Kim, D., Wang, X., Vargas, S., Zhong, P., King, D. S., Inizan, T. J., & Cheng, B. (2025). A universal augmentation framework for long-range electrostatics in machine learning interatomic potentials. Journal of Chemical Theory and Computation. American Chemical Society. https://doi.org/10.1021/acs.jctc.5c01400 chicago: Kim, Dongjin, Xiaoyu Wang, Santiago Vargas, Peichen Zhong, Daniel S. King, Theo Jaffrelot Inizan, and Bingqing Cheng. “A Universal Augmentation Framework for Long-Range Electrostatics in Machine Learning Interatomic Potentials.” Journal of Chemical Theory and Computation. American Chemical Society, 2025. https://doi.org/10.1021/acs.jctc.5c01400. ieee: D. Kim et al., “A universal augmentation framework for long-range electrostatics in machine learning interatomic potentials,” Journal of Chemical Theory and Computation, vol. 21, no. 24. American Chemical Society, pp. 12709–12724, 2025. ista: Kim D, Wang X, Vargas S, Zhong P, King DS, Inizan TJ, Cheng B. 2025. A universal augmentation framework for long-range electrostatics in machine learning interatomic potentials. Journal of Chemical Theory and Computation. 21(24), 12709–12724. mla: Kim, Dongjin, et al. “A Universal Augmentation Framework for Long-Range Electrostatics in Machine Learning Interatomic Potentials.” Journal of Chemical Theory and Computation, vol. 21, no. 24, American Chemical Society, 2025, pp. 12709–24, doi:10.1021/acs.jctc.5c01400. short: D. Kim, X. Wang, S. Vargas, P. Zhong, D.S. King, T.J. Inizan, B. Cheng, Journal of Chemical Theory and Computation 21 (2025) 12709–12724. corr_author: '1' das_tickbox: '1' dataavailabilitystatement: The training sets, training scripts, and trained potentials are available at https://github.com/ChengUCB/les_fit. The LES library is publicly available at https://github.com/ChengUCB/les. The CACE package with the LES implementation is available at https://github.com/BingqingCheng/cace. The MACE package with the LES implementation is available at https://github.com/ACEsuit/mace. The NequIP and Allegro LES extension package is available at https://github.com/ChengUCB/NequIP-LES. The MatGL package with the LES implementation is available at https://github.com/ChengUCB/matgl. The UMA package with the LES implementation is available at https://github.com/santi921/fairchem/tree/les_branch. date_created: 2026-01-04T23:01:33Z date_published: 2025-12-10T00:00:00Z date_updated: 2026-08-07T09:35:25Z day: '10' department: - _id: GradSch - _id: BiCh doi: 10.1021/acs.jctc.5c01400 external_id: arxiv: - '2507.14302' pmid: - '41368735 ' fulldoi: https://doi.org/10.1021/acs.jctc.5c01400 intvolume: ' 21' issue: '24' language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.48550/arXiv.2507.14302 month: '12' oa: 1 oa_version: Preprint page: 12709-12724 pmid: 1 publication: Journal of Chemical Theory and Computation publication_identifier: eissn: - 1549-9626 issn: - 1549-9618 publication_status: published publisher: American Chemical Society quality_controlled: '1' researchdata_availability: no scopus_import: '1' status: public supplementarymaterial: no title: A universal augmentation framework for long-range electrostatics in machine learning interatomic potentials type: journal_article user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345 volume: 21 year: '2025' ... --- OA_place: publisher _id: '20074' abstract: - lang: eng text: "Prenatal immune challenges pose significant risks to human embryonic brain and eye development. However, we still lack knowledge about the safe usage of anti-inflammatory drugs during pregnancy. Human induced pluripotent stem cell (hIPSC)-derived brain organoid models provide a unique opportunity to investigate neuronal development and have started to explore functional consequences upon viral infection. However, brain organoids usually lack microglia, the brain-resident immune cells. They are present in the early human embryonic brain and actively participate in neuronal circuit development. At the same time, microglia are known for their immune-sensing properties and will influence viral-mediated effects. In my thesis, I was interested to study the multifunctional role of human microglia during retinal development. \r\nIn chapter 1, I characterize the innate occurrence of IBA1+-microglia-like cells within the retinal organoid differentiation (Bartalska et al., 2022). Therefore, we differentiate hIPSC using an unguided retinal organoid differentiation protocol and observe the presence of IBA1+-microglia-like cells alongside retinal cups between week 3 and 4 in 2.5D culture. However, instead of infiltrating the neuroectodermal sides, they enrich within non-pigmented, 3D-cystic compartments that develop in low numbers parallel to 3D-retinal organoids. To enrich for IBA1+-microglia precursors (preMG), we guided the differentiation with a low-dosed BMP4 application, which prevents retinal cup development and enhances microglia and 3D-cysts formation. We characterize the differentiated preMG for their microglia-like identity and validated their functionality. In parallel, mass spectrometry identifies the 3D-cysts to express mesenchymal and epithelial markers. We confirm that comparable 3D-cysts are also the preferential environment for IBA1+-microglia-like cells within the unguided retinal organoid differentiation. \r\nIn chapter 2, I investigate how microglia influence retinal development and whether they contribute to viral-mediated consequences (Schmied et al., 2025). Here, we assemble preMG, which we have characterized in chapter 1, into 3D-retinal organoids. Once the outer plexiform layer forms, microglia-like cells (iMG) populate them and interact with retinal cell types. However, at this developmental stage, the ganglion cell number decreases in 3D-retinal organoids. Thus, we adapted the model into 2D which promotes their survival. Integrated iMG engulf ganglion cells and control their cell number. In parallel, we apply the immunostimulant POLY(I:C) to mimic a fetal viral infection. Although POLY(I:C) stimulation affects iMG phenotype, it does not influence their interaction with ganglion cells. Furthermore, iMG presence significantly contributes to the supernatant’s inflammatory secretome and increases retinal cell proliferation. Simultaneous exposure to the non-steroidal anti-inflammatory drug (NSAID) ibuprofen dampens POLY(I:C)-mediated consequences of the iMG phenotype and ameliorates cell proliferation. Remarkably, while POLY(I:C) disrupts neuronal calcium dynamics independent of iMG presence, ibuprofen rescues this effect only in the presence of iMG. Mechanistically, ibuprofen blocks the enzymes cyclooxygenase 1 and 2 (COX1/ PTGS1 and COX2/ PTGS2) simultaneously, from which iMG predominantly express COX1. Selective inhibition of COX1 does not restore the calcium peak amplitude upon POLY(I:C) stimulation, indicating ibuprofen’s effect depends on the presence and interplay of both, COX1 and COX2. \r\nIn summary, we characterized the 3D-retinal organoid model for the occurrence of IBA1+-microglia like cells. As the innately developing IBA1+-cells enrich in mesenchymal over retinal structures, we optimized a protocol to differentiate IBA1+-microglia precursors. By combining these two models we generate microglia-assembled retinal organoids. Our results underscore the importance of microglia during neurodevelopment, in the context of prenatal immune challenges and provide insight into the mechanisms by which ibuprofen exerts its protective effects during embryonic development." alternative_title: - ISTA Thesis article_processing_charge: No author: - first_name: Verena full_name: Hübschmann, Verena id: 32B7C918-F248-11E8-B48F-1D18A9856A87 last_name: Hübschmann citation: ama: Schmied V. Human microglia impact neuronal development in retinal organoids. 2025. doi:10.15479/AT-ISTA-20074 apa: Schmied, V. (2025). Human microglia impact neuronal development in retinal organoids. Institute of Science and Technology Austria. https://doi.org/10.15479/AT-ISTA-20074 chicago: Schmied, Verena. “Human Microglia Impact Neuronal Development in Retinal Organoids.” Institute of Science and Technology Austria, 2025. https://doi.org/10.15479/AT-ISTA-20074. ieee: V. Schmied, “Human microglia impact neuronal development in retinal organoids,” Institute of Science and Technology Austria, 2025. ista: Schmied V. 2025. Human microglia impact neuronal development in retinal organoids. Institute of Science and Technology Austria. mla: Schmied, Verena. Human Microglia Impact Neuronal Development in Retinal Organoids. Institute of Science and Technology Austria, 2025, doi:10.15479/AT-ISTA-20074. short: V. Schmied, Human Microglia Impact Neuronal Development in Retinal Organoids, Institute of Science and Technology Austria, 2025. corr_author: '1' date_created: 2025-07-24T12:37:22Z date_published: 2025-07-24T00:00:00Z date_updated: 2026-08-12T08:45:16Z day: '24' ddc: - '570' degree_awarded: PhD department: - _id: GradSch - _id: SaSi doi: 10.15479/AT-ISTA-20074 doi_confirm: '1' file: - access_level: closed checksum: d09f9984002353ad7442358394919bf3 content_type: application/x-zip-compressed creator: vhuebsch date_created: 2025-07-30T08:47:53Z date_updated: 2025-07-30T08:47:53Z file_id: '20086' file_name: PhD_Thesis_Schmied.zip file_size: 43566093 relation: source_file - access_level: open_access checksum: 4833690d7283c587f518ba98eeb2c946 content_type: application/pdf creator: vhuebsch date_created: 2025-07-30T08:47:46Z date_updated: 2025-07-30T09:29:09Z file_id: '20087' file_name: PhD_Thesis_Schmied.pdf file_size: 13120922 relation: main_file file_date_updated: 2025-07-30T09:29:09Z fulldoi: https://doi.org/10.15479/AT-ISTA-20074 has_accepted_license: '1' language: - iso: eng license: https://creativecommons.org/licenses/by/4.0/ month: '07' oa: 1 oa_version: Published Version page: '151' project: - _id: 9B99D380-BA93-11EA-9121-9846C619BF3A grant_number: SC19-017 name: How human microglia shape developing neurons during health and inflammation publication_identifier: isbn: - 978-3-99078-060-2 issn: - 2663-337X publication_status: published publisher: Institute of Science and Technology Austria related_material: record: - id: '11478' relation: part_of_dissertation status: public - id: '19593' relation: part_of_dissertation status: public status: public supervisor: - first_name: Sandra full_name: Siegert, Sandra id: 36ACD32E-F248-11E8-B48F-1D18A9856A87 last_name: Siegert orcid: 0000-0001-8635-0877 title: Human microglia impact neuronal development in retinal organoids 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: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2025' ... --- DOAJ_listed: '1' OA_place: publisher OA_type: gold PlanS_conform: '1' _id: '20342' abstract: - lang: eng text: Safety and liveness stand as fundamental concepts in formal languages, playing a key role in verification. The safety-liveness classification of boolean properties characterizes whether a given property can be falsified by observing a finite prefix of an infinite computation trace (always for safety, never for liveness). In the quantitative setting, properties are arbitrary functions from infinite words to partially-ordered domains. Extending this paradigm to the quantitative domain, where properties are arbitrary functions mapping infinite words to partially-ordered domains, we introduce and study the notions of quantitative safety and liveness. First, we formally define quantitative safety and liveness, and prove that our definitions induce conservative quantitative generalizations of both the safety-progress hierarchy and the safety-liveness decomposition of boolean properties. Consequently, like their boolean counterparts, quantitative properties can be min-decomposed into safety and liveness parts, or alternatively, max-decomposed into co-safety and co-liveness parts. We further establish a connection between quantitative safety and topological continuity and provide alternative characterizations of quantitative safety and liveness in terms of their boolean analogs. Second, we instantiate our framework with the specific classes of quantitative properties expressed by automata. These quantitative automata contain finitely many states and rational-valued transition weights, and their common value functions Inf, Sup, LimInf, LimSup, LimInfAvg, LimSupAvg, and DSum map infinite words into the totally-ordered domain of real numbers. For all common value functions, we provide a procedure for deciding whether a given automaton is safe or live, we show how to construct its safety closure, and we present a min-decomposition into safe and live automata. acknowledgement: This work was supported in part by the ERC-2020-AdG 101020093 and the Israel Science Foundation grant 2410/22. N. Mazzocchi was affiliated with ISTA when this work was submitted for publication. article_number: '13149' article_processing_charge: Yes article_type: original arxiv: 1 author: - first_name: Udi full_name: Boker, Udi id: 31E297B6-F248-11E8-B48F-1D18A9856A87 last_name: Boker - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000-0002-2985-7724 - first_name: Nicolas Adrien full_name: Mazzocchi, Nicolas Adrien id: b26baa86-3308-11ec-87b0-8990f34baa85 last_name: Mazzocchi - first_name: Naci E full_name: Sarac, Naci E id: 8C6B42F8-C8E6-11E9-A03A-F2DCE5697425 last_name: Sarac citation: ama: Boker U, Henzinger TA, Mazzocchi NA, Sarac NE. Safety and liveness of quantitative properties and automata. Logical Methods in Computer Science. 2025;21(2). doi:10.46298/lmcs-21(2:2)2025 apa: Boker, U., Henzinger, T. A., Mazzocchi, N. A., & Sarac, N. E. (2025). Safety and liveness of quantitative properties and automata. Logical Methods in Computer Science. EPI Sciences. https://doi.org/10.46298/lmcs-21(2:2)2025 chicago: Boker, Udi, Thomas A Henzinger, Nicolas Adrien Mazzocchi, and Naci E Sarac. “Safety and Liveness of Quantitative Properties and Automata.” Logical Methods in Computer Science. EPI Sciences, 2025. https://doi.org/10.46298/lmcs-21(2:2)2025. ieee: U. Boker, T. A. Henzinger, N. A. Mazzocchi, and N. E. Sarac, “Safety and liveness of quantitative properties and automata,” Logical Methods in Computer Science, vol. 21, no. 2. EPI Sciences, 2025. ista: Boker U, Henzinger TA, Mazzocchi NA, Sarac NE. 2025. Safety and liveness of quantitative properties and automata. Logical Methods in Computer Science. 21(2), 13149. mla: Boker, Udi, et al. “Safety and Liveness of Quantitative Properties and Automata.” Logical Methods in Computer Science, vol. 21, no. 2, 13149, EPI Sciences, 2025, doi:10.46298/lmcs-21(2:2)2025. short: U. Boker, T.A. Henzinger, N.A. Mazzocchi, N.E. Sarac, Logical Methods in Computer Science 21 (2025). corr_author: '1' date_created: 2025-09-11T12:17:52Z date_published: 2025-04-08T00:00:00Z date_updated: 2026-08-12T08:46:05Z day: '08' ddc: - '000' department: - _id: GradSch - _id: ToHe doi: 10.46298/lmcs-21(2:2)2025 ec_funded: 1 external_id: arxiv: - '2307.06016' isi: - '001468887900001' file: - access_level: open_access checksum: 0b4d477bd981379724c35a4de2c176e5 content_type: application/pdf creator: esarac date_created: 2025-09-11T12:17:12Z date_updated: 2025-09-11T12:17:12Z file_id: '20343' file_name: 2307.06016.pdf file_size: 709584 relation: main_file success: 1 file_date_updated: 2025-09-11T12:17:12Z fulldoi: https://doi.org/10.46298/lmcs-21(2:2)2025 has_accepted_license: '1' intvolume: ' 21' isi: 1 issue: '2' language: - iso: eng month: '04' 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: Logical Methods in Computer Science publication_identifier: eissn: - 1860-5974 publication_status: published publisher: EPI Sciences quality_controlled: '1' related_material: record: - id: '13221' relation: earlier_version status: public - id: '20147' relation: dissertation_contains status: public scopus_import: '1' status: public title: Safety and liveness of quantitative properties and automata 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: 21 year: '2025' ... --- OA_place: publisher _id: '20167' acknowledged_ssus: - _id: Bio - _id: LifeSc acknowledgement: "This work was supported by EMBO (ALTF 302-2019 to Niko Amin-Wetzel), the FWF\r\n(ESPRIT PR1054E140 to Niko Amin-Wetzel), the European Research Council\r\n(Advanced Grant 269058 to Mario de Bono) and Wellcome (209504/A/17/Z\r\nInvestigator Award to Mario de Bono). " alternative_title: - ISTA Thesis article_processing_charge: No author: - first_name: Hanna full_name: Schön, Hanna id: C8E17EDC-D7AA-11E9-B7B7-45ECE5697425 last_name: Schön citation: ama: Schön H. The ER complex SUTU-7/MACO-1 regulates the fate of mRNAs encoding GPCRs. 2025. doi:10.15479/AT-ISTA-20167 apa: Schön, H. (2025). The ER complex SUTU-7/MACO-1 regulates the fate of mRNAs encoding GPCRs. Institute of Science and Technology Austria. https://doi.org/10.15479/AT-ISTA-20167 chicago: Schön, Hanna. “The ER Complex SUTU-7/MACO-1 Regulates the Fate of MRNAs Encoding GPCRs.” Institute of Science and Technology Austria, 2025. https://doi.org/10.15479/AT-ISTA-20167. ieee: H. Schön, “The ER complex SUTU-7/MACO-1 regulates the fate of mRNAs encoding GPCRs,” Institute of Science and Technology Austria, 2025. ista: Schön H. 2025. The ER complex SUTU-7/MACO-1 regulates the fate of mRNAs encoding GPCRs. Institute of Science and Technology Austria. mla: Schön, Hanna. The ER Complex SUTU-7/MACO-1 Regulates the Fate of MRNAs Encoding GPCRs. Institute of Science and Technology Austria, 2025, doi:10.15479/AT-ISTA-20167. short: H. Schön, The ER Complex SUTU-7/MACO-1 Regulates the Fate of MRNAs Encoding GPCRs, Institute of Science and Technology Austria, 2025. corr_author: '1' date_created: 2025-08-13T11:13:13Z date_published: 2025-08-13T00:00:00Z date_updated: 2026-08-13T13:05:37Z day: '13' ddc: - '570' degree_awarded: PhD department: - _id: GradSch - _id: MaDe doi: 10.15479/AT-ISTA-20167 doi_confirm: '1' file: - access_level: closed checksum: b40c74404b8d9593802dabf57bfdf10f content_type: application/vnd.openxmlformats-officedocument.wordprocessingml.document creator: hschoen date_created: 2025-09-08T14:33:50Z date_updated: 2025-09-09T08:57:04Z file_id: '20311' file_name: 2025_Schoen_Hanna_Thesis.docx file_size: 78812587 relation: source_file - access_level: closed checksum: 16abc3ff66396ce2457fe07ffa8bed90 content_type: application/pdf creator: hschoen date_created: 2025-09-11T14:20:59Z date_updated: 2026-08-13T13:05:36Z embargo: 2027-03-15 embargo_to: open_access file_id: '20347' file_name: 2025_Schoen_Hanna_Thesis.pdf file_size: 9667057 relation: main_file file_date_updated: 2026-08-13T13:05:36Z fulldoi: https://doi.org/10.15479/AT-ISTA-20167 has_accepted_license: '1' language: - iso: eng month: '08' oa_version: Published Version page: '171' project: - _id: 23870BE8-32DE-11EA-91FC-C7463DDC885E grant_number: 209504/A/17/Z name: Molecular mechanisms of neural circuit function - _id: 23813290-32DE-11EA-91FC-C7463DDC885E grant_number: ALTF 302-2019 name: Control of gene expression at the endoplasmic reticulum publication_identifier: isbn: - 978-3-99078-061-9 issn: - 2663-337X publication_status: published publisher: Institute of Science and Technology Austria status: public supervisor: - first_name: Mario full_name: de Bono, Mario id: 4E3FF80E-F248-11E8-B48F-1D18A9856A87 last_name: de Bono orcid: 0000-0001-8347-0443 title: The ER complex SUTU-7/MACO-1 regulates the fate of mRNAs encoding GPCRs 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: '2025' ... --- OA_place: publisher OA_type: hybrid PlanS_conform: '1' _id: '20538' abstract: - lang: eng text: In this study, we describe an integrated approach for methyl group assignment comprising precursor-based selective methyl group labeling, a novel pulse sequence for methyl to backbone coherence transfer and chemical shift predictions using UCBShift 2.0. The utility of this novel α-ketoacid isotopologue is shown by the adaptation of an HMBC-HMQC pulse sequence that simultaneously connects geminal methyl groups of leucine and valine residues to each other and to the protein backbone. By additional 13C,2H-labeling of residues other than valine and leucine residues of the protein, important chemical shift information about neighboring residues (following valine and leucine residues) can be achieved. Thus, different valine and leucine residues in a protein can be characterized as a specific chemical shift vector. Frequency matching with predicted chemical shifts via UCBShift 2.0 using experimental data taken from a subset of the BMRB database revealed a correct assignment performance of about 90%. With applications to proteins of 60.2 kDa and 134 kDa (4 × 33.5 kDa) in size, we demonstrate that the approach provides valuable information even for very large proteins. acknowledged_ssus: - _id: NMR - _id: LifeSc acknowledgement: A.L.P and G.T were funded by the “New Ideas” program by Vienna Doctoral School in Chemistry. S.K. was funded by the Austrian Science Fund FWF P35098-B. This work was supported financially by the Austrian Science Fund (FWF, grant numbers I06223 and I5812-B, “AlloSpace”). This research was supported by the Scientific Service Units (SSU) of Institute of Science and Technology Austria (ISTA) through resources provided by the Nuclear Magnetic Resonance Facility and the Lab Support Facility (LSF). We thank Celina Sailer for assistance with the analysis of the NMR spectrum of HsTom70. article_number: '169465' article_processing_charge: Yes (in subscription journal) article_type: original author: - first_name: Sonja full_name: Knödlstorfer, Sonja last_name: Knödlstorfer - first_name: Giorgia full_name: Toscano, Giorgia id: 334a5e40-8747-11f0-b671-ba1f5154b4b4 last_name: Toscano - first_name: Aleksandra L. full_name: Ptaszek, Aleksandra L. last_name: Ptaszek - first_name: Georg full_name: Kontaxis, Georg last_name: Kontaxis - first_name: Federico full_name: Napoli, Federico id: d42e08e7-f4fc-11eb-af0a-d71e26138f1b last_name: Napoli orcid: 0000-0002-9043-136X - first_name: Jakob full_name: Schneider, Jakob id: 64368429-eb97-11eb-a6c2-c980b1f44415 last_name: Schneider - first_name: Katharina full_name: Maier, Katharina last_name: Maier - first_name: Anna full_name: Kapitonova, Anna id: 9fb2a840-89e1-11ee-a8b7-cc5c7ba62471 last_name: Kapitonova - first_name: Roman J. full_name: Lichtenecker, Roman J. last_name: Lichtenecker - first_name: Paul full_name: Schanda, Paul id: 7B541462-FAF6-11E9-A490-E8DFE5697425 last_name: Schanda orcid: 0000-0002-9350-7606 - first_name: Robert full_name: Konrat, Robert last_name: Konrat citation: ama: Knödlstorfer S, Toscano G, Ptaszek AL, et al. A novel HMBC-CC-HMQC NMR strategy for methyl assignment using triple-13C-labeled α-ketoisovalerate integrated with UCBShift 2.0. Journal of Molecular Biology. 2025;437(23). doi:10.1016/j.jmb.2025.169465 apa: Knödlstorfer, S., Toscano, G., Ptaszek, A. L., Kontaxis, G., Napoli, F., Schneider, J., … Konrat, R. (2025). A novel HMBC-CC-HMQC NMR strategy for methyl assignment using triple-13C-labeled α-ketoisovalerate integrated with UCBShift 2.0. Journal of Molecular Biology. Elsevier. https://doi.org/10.1016/j.jmb.2025.169465 chicago: Knödlstorfer, Sonja, Giorgia Toscano, Aleksandra L. Ptaszek, Georg Kontaxis, Federico Napoli, Jakob Schneider, Katharina Maier, et al. “A Novel HMBC-CC-HMQC NMR Strategy for Methyl Assignment Using Triple-13C-Labeled α-Ketoisovalerate Integrated with UCBShift 2.0.” Journal of Molecular Biology. Elsevier, 2025. https://doi.org/10.1016/j.jmb.2025.169465. ieee: S. Knödlstorfer et al., “A novel HMBC-CC-HMQC NMR strategy for methyl assignment using triple-13C-labeled α-ketoisovalerate integrated with UCBShift 2.0,” Journal of Molecular Biology, vol. 437, no. 23. Elsevier, 2025. ista: Knödlstorfer S, Toscano G, Ptaszek AL, Kontaxis G, Napoli F, Schneider J, Maier K, Kapitonova A, Lichtenecker RJ, Schanda P, Konrat R. 2025. A novel HMBC-CC-HMQC NMR strategy for methyl assignment using triple-13C-labeled α-ketoisovalerate integrated with UCBShift 2.0. Journal of Molecular Biology. 437(23), 169465. mla: Knödlstorfer, Sonja, et al. “A Novel HMBC-CC-HMQC NMR Strategy for Methyl Assignment Using Triple-13C-Labeled α-Ketoisovalerate Integrated with UCBShift 2.0.” Journal of Molecular Biology, vol. 437, no. 23, 169465, Elsevier, 2025, doi:10.1016/j.jmb.2025.169465. short: S. Knödlstorfer, G. Toscano, A.L. Ptaszek, G. Kontaxis, F. Napoli, J. Schneider, K. Maier, A. Kapitonova, R.J. Lichtenecker, P. Schanda, R. Konrat, Journal of Molecular Biology 437 (2025). date_created: 2025-10-26T23:01:35Z date_published: 2025-12-01T00:00:00Z date_updated: 2026-08-13T14:19:02Z day: '01' ddc: - '540' department: - _id: PaSc - _id: GradSch doi: 10.1016/j.jmb.2025.169465 external_id: pmid: - '41016549' file: - access_level: open_access checksum: feb92f9c79032c261165f4ca573f444a content_type: application/pdf creator: dernst date_created: 2025-12-30T10:29:08Z date_updated: 2025-12-30T10:29:08Z file_id: '20915' file_name: 2025_JourMolecularBiology_Knoedlstorfer.pdf file_size: 3076611 relation: main_file success: 1 file_date_updated: 2025-12-30T10:29:08Z fulldoi: https://doi.org/10.1016/j.jmb.2025.169465 has_accepted_license: '1' intvolume: ' 437' issue: '23' language: - iso: eng month: '12' oa: 1 oa_version: Published Version pmid: 1 project: - _id: bdb9578d-d553-11ed-ba76-ed5d39fce6f0 grant_number: I06223 name: Structure and mechanism of the mitochondrial MIM insertase - _id: eb9c82eb-77a9-11ec-83b8-aadd536561cf grant_number: I05812 name: AlloSpace. The emergence and mechanisms of allostery publication: Journal of Molecular Biology publication_identifier: eissn: - 1089-8638 issn: - 0022-2836 publication_status: published publisher: Elsevier quality_controlled: '1' scopus_import: '1' status: public title: A novel HMBC-CC-HMQC NMR strategy for methyl assignment using triple-13C-labeled α-ketoisovalerate integrated with UCBShift 2.0 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: 437 year: '2025' ... --- OA_place: repository OA_type: green _id: '19398' abstract: - lang: eng text: Receptor-like kinases (RLKs), particularly the Transmembrane Kinase (TMK) family, play essential roles in signaling and development, with TMKs being key components of auxin perception and downstream phosphorylation events. While TMKs’ involvement in auxin canalization, a process essential for vasculature formation and regeneration, has been established, nonetheless, the additional signaling and regulatory partners remain poorly understood. In this study, we identify and characterize seven leucine-rich repeat RLKs (TINT1–TINT7) as novel interactors of TMK1, revealing their diverse evolutionary, structural, and functional characteristics. Our results show that TINTs interact with TMK1 and highlight their roles in regulating various developmental processes. Majority of TINTs contributes, together with TMK1, to auxin canalization, with TINT5 linking TMK1 to other canalization component CAMEL. Beyond canalization, we also establish the role of TINT-TMK1 interactions in processes such as stomatal movement and the hypocotyl’s gravitropic response. These findings suggest that TINTs, through their interaction with TMK1, are integral components of various signaling networks, contributing to both auxin canalization and broader plant development. acknowledged_ssus: - _id: Bio - _id: LifeSc acknowledgement: We deeply appreciate M. Wrzaczek’s constructive input and insightful discussions, which significantly enriched this work. We thank L. Fiedler for helping with the heat map and for the discussions. We also thank the facilities at ISTA, the imaging and optics (IOF) and Lab Support (LSF) facilities for their service and assistance. article_processing_charge: No author: - first_name: Aline full_name: Monzer, Aline id: 2DB5D88C-D7B3-11E9-B8FD-7907E6697425 last_name: Monzer - first_name: Ewa full_name: Mazur, Ewa last_name: Mazur - first_name: Lesia full_name: Rodriguez Solovey, Lesia id: 3922B506-F248-11E8-B48F-1D18A9856A87 last_name: Rodriguez Solovey orcid: 0000-0002-7244-7237 - first_name: Michelle C full_name: Gallei, Michelle C id: 35A03822-F248-11E8-B48F-1D18A9856A87 last_name: Gallei orcid: 0000-0003-1286-7368 - first_name: Minxia full_name: Zou, Minxia id: 5c243f41-03f3-11ec-841c-96faf48a7ef9 last_name: Zou - first_name: Michael full_name: Smejkal, Michael id: 79a5a1be-04a3-11f0-ba18-a1730e0b58e9 last_name: Smejkal - first_name: Ema full_name: Cervenova, Ema id: 9f185b95-04a3-11f0-8245-f5e32eeb470f last_name: Cervenova - first_name: Jiří full_name: Friml, Jiří id: 4159519E-F248-11E8-B48F-1D18A9856A87 last_name: Friml orcid: 0000-0002-8302-7596 citation: ama: Monzer A, Mazur E, Rodriguez Solovey L, et al. TMK interacting network of receptor like kinases for auxin canalization and beyond. bioRxiv. doi:10.1101/2025.02.28.640727 apa: Monzer, A., Mazur, E., Rodriguez Solovey, L., Gallei, M. C., Zou, M., Smejkal, M., … Friml, J. (n.d.). TMK interacting network of receptor like kinases for auxin canalization and beyond. bioRxiv. https://doi.org/10.1101/2025.02.28.640727 chicago: Monzer, Aline, Ewa Mazur, Lesia Rodriguez Solovey, Michelle C Gallei, Minxia Zou, Michael Smejkal, Ema Cervenova, and Jiří Friml. “TMK Interacting Network of Receptor like Kinases for Auxin Canalization and Beyond.” BioRxiv, n.d. https://doi.org/10.1101/2025.02.28.640727. ieee: A. Monzer et al., “TMK interacting network of receptor like kinases for auxin canalization and beyond,” bioRxiv. . ista: Monzer A, Mazur E, Rodriguez Solovey L, Gallei MC, Zou M, Smejkal M, Cervenova E, Friml J. TMK interacting network of receptor like kinases for auxin canalization and beyond. bioRxiv, 10.1101/2025.02.28.640727. mla: Monzer, Aline, et al. “TMK Interacting Network of Receptor like Kinases for Auxin Canalization and Beyond.” BioRxiv, doi:10.1101/2025.02.28.640727. short: A. Monzer, E. Mazur, L. Rodriguez Solovey, M.C. Gallei, M. Zou, M. Smejkal, E. Cervenova, J. Friml, BioRxiv (n.d.). corr_author: '1' das_tickbox: '1' date_created: 2025-03-12T14:28:53Z date_published: 2025-03-02T00:00:00Z date_updated: 2026-08-14T09:33:45Z day: '02' ddc: - '580' department: - _id: GradSch - _id: JiFr - _id: EvBe doi: 10.1101/2025.02.28.640727 fulldoi: https://doi.org/10.1101/2025.02.28.640727 has_accepted_license: '1' language: - iso: eng license: https://creativecommons.org/licenses/by-nc-nd/4.0/ main_file_link: - open_access: '1' url: https://doi.org/10.1101/2025.02.28.640727 month: '03' oa: 1 oa_version: Published Version publication: bioRxiv publication_status: draft related_material: record: - id: '19395' relation: dissertation_contains status: public status: public title: TMK interacting network of receptor like kinases for auxin canalization and beyond 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: preprint user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2025' ... --- OA_place: publisher _id: '19684' abstract: - lang: eng text: "The overarching goal of this thesis is to break down the complexity of turbulent flows in terms of enumerable, coherent structures and patterns. In a five-paper series, we adopt a variety of perspectives and techniques to relate the properties of systems of increasing complexity to their underlying coherent structures. \r\n\r\nInitially, we take a dynamical systems point of view, seeing turbulent flow as a chaotic trajectory bouncing between exact unstable solutions of the underlying equations of motion. Using persistent homology, the main tool of topological data analysis capturing the persistence across scales of topological features in a point cloud, we introduce a method that quantifies visits of turbulent trajectories to unstable time-periodic solutions, also called periodic orbits. We demonstrate this method first in the Rössler and Kuramoto–Sivashinsky systems. Using this method in 3D Kolmogorov flow, we extract a Markov chain from turbulent data, where each node corresponds to the neighbourhood of a periodic orbit. The invariant distribution of this Markov chain reproduces expectation values on turbulent data when it is used to weight averages on the respective periodic orbits.\r\n\r\nIn more realistic, wall-bounded settings, such as plane-Couette flow (pcf) driven by the relative motion of the walls, or plane-Poiseuille flow (ppf) driven by a pressure gradient, finding exact solutions is difficult. We use dynamic mode decomposition (DMD), a dimensionality reduction method for sequential data, to identify and approximate low-dimensional dynamics without knowing any exact solutions. Most spatially-extended systems are equivariant under translations, and in such cases spatial drifts dominate DMD, hindering its use in the search for and modelling of low-dimensional dynamics. We augment DMD with a symmetry reduction method trained on turbulent data to stop it from seeing translations as a feature, improving its ability to extract dynamical information in translation-equivariant systems. We find segments of turbulent trajectories that linearize well with their symmetry-reduced DMD spectra, akin to dynamics near exact solutions. Searching for harmonics in the spectra gives leads for periodic orbits with spatial drifts, one of which converges to a new solution.\r\n\r\nIn larger domains, turbulence can localize and coexist with surrounding laminar flow. Our preceding approaches are global, taking all of a domain into account at once, and cannot readily treat each localized patch individually. Working first in a minimal oblique domain that can host a single 1D-localized turbulent patch, we find that turbulence in ppf is connected to a stable periodic orbit at a flow velocity much lower than when turbulence is first onset. We show that, well in advance of sustained turbulence, chaos sets in explosively, and for long time horizons, time series are consistent with that of a random process.\r\n\r\nFinally, in much larger domains, we study and compare 2D-localized turbulence that appears as large-scale inclined structures, called stripes, in ppf and pcf. While appearing similar, we find that stripes in these two settings differ significantly in terms of how they sustain themselves, and in higher velocities, how they proliferate." acknowledged_ssus: - _id: ScienComp acknowledgement: "The work in this thesis was supported by a grant from the Simons Foundation (662960, BH).\r\n" alternative_title: - ISTA Thesis article_processing_charge: No author: - first_name: Gökhan full_name: Yalniz, Gökhan id: 66E74FA2-D8BF-11E9-8249-8DE2E5697425 last_name: Yalniz orcid: 0000-0002-8490-9312 citation: ama: 'Yalniz G. Transition to turbulence: Data-, solution-, and pattern-driven approaches. 2025. doi:10.15479/AT-ISTA-19684' apa: 'Yalniz, G. (2025). Transition to turbulence: Data-, solution-, and pattern-driven approaches. Institute of Science and Technology Austria. https://doi.org/10.15479/AT-ISTA-19684' chicago: 'Yalniz, Gökhan. “Transition to Turbulence: Data-, Solution-, and Pattern-Driven Approaches.” Institute of Science and Technology Austria, 2025. https://doi.org/10.15479/AT-ISTA-19684.' ieee: 'G. Yalniz, “Transition to turbulence: Data-, solution-, and pattern-driven approaches,” Institute of Science and Technology Austria, 2025.' ista: 'Yalniz G. 2025. Transition to turbulence: Data-, solution-, and pattern-driven approaches. Institute of Science and Technology Austria.' mla: 'Yalniz, Gökhan. Transition to Turbulence: Data-, Solution-, and Pattern-Driven Approaches. Institute of Science and Technology Austria, 2025, doi:10.15479/AT-ISTA-19684.' short: 'G. Yalniz, Transition to Turbulence: Data-, Solution-, and Pattern-Driven Approaches, Institute of Science and Technology Austria, 2025.' corr_author: '1' date_created: 2025-05-12T15:12:28Z date_published: 2025-05-13T00:00:00Z date_updated: 2026-09-02T08:16:32Z day: '13' ddc: - '514' - '519' - '532' - '004' degree_awarded: PhD department: - _id: GradSch - _id: BjHo doi: 10.15479/AT-ISTA-19684 doi_confirm: '1' file: - access_level: open_access checksum: 0e452642b79f13633f1595bde71a67e3 content_type: application/pdf creator: gyalniz date_created: 2025-05-12T15:13:28Z date_updated: 2025-05-12T15:13:28Z file_id: '19685' file_name: Gökhan Yalnız - PhD thesis.pdf file_size: 20058169 relation: main_file success: 1 - access_level: open_access checksum: 921099d76adab2df784ce12ce41cfb22 content_type: video/mp4 creator: gyalniz date_created: 2025-05-12T15:15:59Z date_updated: 2025-05-12T15:43:28Z description: '3D visualizations of the turbulent flow (left) and the periodic orbits (middle) that are being shadowed along with the local state space projections (right) onto the principal components of the respective periodic orbit. Shown here are the isosurfaces of velocity (red/blue: ±95% of the instantaneous maximum) and vorticity (purple/green: ±65% of the instantaneous maximum) in the x-direction. Markers along the projections are in sync with the 3D visualizations. The movie corresponds to the initial time interval (up to t = 100) of figure 2.2 (a,b); periodic orbits and the state space projections are shown only through the shadowing events indicated in figure 2.2 (b).' file_id: '19686' file_name: Movie 2A.1.mp4 file_size: 37763743 relation: supplementary_material title: Chapter 2 - Movie 2A.1 - access_level: open_access checksum: 0ae5ac7d9896003c0c4207dd746808dc content_type: video/mp4 creator: gyalniz date_created: 2025-05-12T15:16:09Z date_updated: 2025-05-12T15:43:28Z description: 'Turbulent flow (left) in HKW domain and its symmetry reduction (right). Shown here are the isosurfaces of streamwise velocity (red/blue: u = 0.5 max/min u) and streamwise vorticity (green/purple: ω_x = 0.5 max/min ω_x).' file_id: '19687' file_name: Movie 3A.1.mp4 file_size: 3902655 relation: supplementary_material title: Chapter 3 - Movie 3A.1 - access_level: open_access checksum: ef8d270e066c1a9c3cb5ae46acf945e6 content_type: video/mp4 creator: gyalniz date_created: 2025-05-12T15:16:21Z date_updated: 2025-05-12T15:43:28Z description: 'Turbulent flow (left) in P2K domain and its symmetry reduction (right). Shown here are the isosurfaces of streamwise velocity (red/blue: u = 0.5 max/min u) and streamwise vorticity (green/purple: ω_x = 0.5 max/min ω_x).' file_id: '19688' file_name: Movie 3A.2.mp4 file_size: 7043169 relation: supplementary_material title: Chapter 3 - Movie 3A.2 - access_level: open_access checksum: 7ed871f428100d6827ac9b0e8ca8e985 content_type: video/mp4 creator: gyalniz date_created: 2025-05-12T15:16:36Z date_updated: 2025-05-12T15:43:28Z description: 'Relative periodic orbit RPO_79.4 (left) of the plane-Couette flow (HKW domain) and its symmetry reduction (right). Shown here are the isosurfaces of streamwise velocity (red/blue: u = 0.5 max/min u) and streamwise vorticity (green/purple: ω_x = 0.5 max/min ω_x).' file_id: '19689' file_name: Movie 3A.3.mp4 file_size: 7748659 relation: supplementary_material title: Chapter 3 - Movie 3A.3 - access_level: open_access checksum: dd5a252e1da00c8f303588e22e2baeef content_type: video/mp4 creator: gyalniz date_created: 2025-05-12T15:16:50Z date_updated: 2025-05-12T15:43:28Z description: 'Symmetry-reduced flow (left), its SRDMD approximation (middle), and state space projection (right) showing the spiral-out episode in P2K domain (figure 3.6 (b) and figure 3.8 (b)). Shown here are the isosurfaces of streamwise velocity (red/blue: u = 0.5 max/min u) and streamwise vorticity (green/purple: ω_x = 0.5 max/min ω_x).' file_id: '19690' file_name: Movie 3A.4.mp4 file_size: 5873052 relation: supplementary_material title: Chapter 3 - Movie 3A.4 - access_level: open_access checksum: 5ac58b86810698db28cbfc28f351ff70 content_type: video/mp4 creator: gyalniz date_created: 2025-05-12T15:17:11Z date_updated: 2025-05-12T15:43:28Z description: Movie demonstrating the quasi-steady Reynolds number descent from turbulence to a periodic orbit. file_id: '19691' file_name: Movie 4A.1.mp4 file_size: 9209327 relation: supplementary_material title: Chapter 4 - Movie 4A.1 - access_level: open_access checksum: ac877f1e1ef39439911bf37cb1793b8e content_type: video/mp4 creator: gyalniz date_created: 2025-05-12T15:17:43Z date_updated: 2025-05-12T15:43:28Z description: Streamwise velocity fluctuations (from laminar) of plane-Couette flow (Re^C =335) at the y = 0 wall-normal plane in coordinates stationary with respect to the bulk velocity. Here, x is the streamwise direction (the wall at y = 1 moves to the right) and z is the spanwise direction. Time is in advectime time units. Shown is the full (L_x = L_z = 400) domain. file_id: '19692' file_name: Movie 5A.1.mp4 file_size: 5893993 relation: supplementary_material title: Chapter 5 - Movie 5A.1 - access_level: open_access checksum: fd17eabb70129ceaa414e40924d1d2fe content_type: video/mp4 creator: gyalniz date_created: 2025-05-12T15:17:49Z date_updated: 2025-05-12T15:43:28Z description: Streamwise velocity fluctuations (from laminar) of plane-Poiseuille flow (Re^P =660) at the y = 0.5 wall-normal plane in coordinates stationary with respect to the bulk velocity. Here, x is the streamwise direction (the mean negative pressure gradient is to the right) and z is the spanwise direction. Time is in advectime time units. Shown is the full (L_x = L_z = 400) domain. file_id: '19693' file_name: Movie 5A.2.mp4 file_size: 3990352 relation: supplementary_material title: Chapter 5 - Movie 5A.2 - access_level: open_access checksum: 32f904497ab0bbee38f0788d96b91454 content_type: video/mp4 creator: gyalniz date_created: 2025-05-12T15:17:58Z date_updated: 2025-05-12T15:43:28Z description: Streamwise velocity fluctuations (from laminar) of plane-Poiseuille flow (Re^P=660) at the y = 0.5 wall-normal plane in coordinates stationary with respect to the average velocity of the downstream tip of the stripe. Here, x is the streamwise direction (the mean negative pressure gradient is to the right) and z is the spanwise direction. Time is in advectime time units. Shown is a zoom-in of the full (L_x = L_z) domain. file_id: '19694' file_name: Movie 5A.3.mp4 file_size: 5171009 relation: supplementary_material title: Chapter 5 - Movie 5A.3 - access_level: closed checksum: f313261b9bb12dfb943fead8318954c6 content_type: application/x-zip-compressed creator: gyalniz date_created: 2025-05-12T15:27:10Z date_updated: 2025-05-12T15:43:28Z file_id: '19695' file_name: Gökhan Yalnız - PhD thesis.zip file_size: 18991996 relation: source_file file_date_updated: 2025-05-12T15:43:28Z fulldoi: https://doi.org/10.15479/AT-ISTA-19684 has_accepted_license: '1' language: - iso: eng month: '05' oa: 1 oa_version: Published Version page: '155' project: - _id: 238598C6-32DE-11EA-91FC-C7463DDC885E grant_number: '662960' name: Revisiting the Turbulence Problem Using Statistical Mechanics publication_identifier: issn: - 2663-337X publication_status: published publisher: Institute of Science and Technology Austria related_material: record: - id: '9558' relation: part_of_dissertation status: public - id: '12105' relation: part_of_dissertation status: public - id: '13274' relation: part_of_dissertation status: public - id: '14466' relation: part_of_dissertation status: public - id: '7563' relation: part_of_dissertation status: public status: public supervisor: - first_name: Björn full_name: Hof, Björn id: 3A374330-F248-11E8-B48F-1D18A9856A87 last_name: Hof orcid: 0000-0003-2057-2754 title: 'Transition to turbulence: Data-, solution-, and pattern-driven approaches' type: dissertation user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9 year: '2025' ... --- OA_place: publisher OA_type: free access _id: '22825' abstract: - lang: eng text: "The empirical emergence of neural collapse—a surprising symmetry in the feature representations of the training data in the penultimate layer of deep neural\r\nnetworks—has spurred a line of theoretical research aimed at its understanding.\r\nHowever, existing work focuses on data-agnostic models or, when data structure is\r\ntaken into account, it remains limited to multi-layer perceptrons. Our paper fills\r\nboth these gaps by analyzing modern architectures in a data-aware regime: we\r\nprove that global optima of deep regularized transformers and residual networks\r\n(ResNets) with LayerNorm trained with cross entropy or mean squared error loss\r\nare approximately collapsed, and the approximation gets tighter as the depth grows.\r\nMore generally, we formally reduce any end-to-end large-depth ResNet or transformer training into an equivalent unconstrained features model, thus justifying its\r\nwide use in the literature even beyond data-agnostic settings. Our theoretical results\r\nare supported by experiments on computer vision and language datasets showing\r\nthat, as the depth grows, neural collapse indeed becomes more prominent." acknowledged_ssus: - _id: ScienComp acknowledgement: "M. M. and P. S. are funded by the European Union (ERC, INF2\r\n, project number 101161364). Views\r\nand opinions expressed are however those of the author(s) only and do not necessarily reflect those\r\nof the European Union or the European Research Council Executive Agency. Neither the European\r\nUnion nor the granting authority can be held responsible for them. This research was supported\r\nby the Scientific Service Units (SSU) of ISTA through resources provided by Scientific Computing (SciComp)." alternative_title: - Advances in Neural Information Processing Systems article_processing_charge: No arxiv: 1 author: - first_name: Peter full_name: Súkeník, Peter id: d64d6a8d-eb8e-11eb-b029-96fd216dec3c last_name: Súkeník - first_name: Christoph full_name: Lampert, Christoph id: 40C20FD2-F248-11E8-B48F-1D18A9856A87 last_name: Lampert orcid: 0000-0001-8622-7887 - first_name: Marco full_name: Mondelli, Marco id: 27EB676C-8706-11E9-9510-7717E6697425 last_name: Mondelli orcid: 0000-0002-3242-7020 citation: ama: 'Súkeník P, Lampert C, Mondelli M. Neural collapse is globally optimal in deep regularized ResNets and transformers. In: 39th Conference on Neural Information Processing Systems. Vol 38. Neural Information Processing Systems Foundation; 2025:48646-48677. doi:10.52202/085713-1450' apa: 'Súkeník, P., Lampert, C., & Mondelli, M. (2025). Neural collapse is globally optimal in deep regularized ResNets and transformers. In 39th Conference on Neural Information Processing Systems (Vol. 38, pp. 48646–48677). San Diego, CA, United States: Neural Information Processing Systems Foundation. https://doi.org/10.52202/085713-1450' chicago: Súkeník, Peter, Christoph Lampert, and Marco Mondelli. “Neural Collapse Is Globally Optimal in Deep Regularized ResNets and Transformers.” In 39th Conference on Neural Information Processing Systems, 38:48646–77. Neural Information Processing Systems Foundation, 2025. https://doi.org/10.52202/085713-1450. ieee: P. Súkeník, C. Lampert, and M. Mondelli, “Neural collapse is globally optimal in deep regularized ResNets and transformers,” in 39th Conference on Neural Information Processing Systems, San Diego, CA, United States, 2025, vol. 38, pp. 48646–48677. ista: 'Súkeník P, Lampert C, Mondelli M. 2025. Neural collapse is globally optimal in deep regularized ResNets and transformers. 39th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems, Advances in Neural Information Processing Systems, vol. 38, 48646–48677.' mla: Súkeník, Peter, et al. “Neural Collapse Is Globally Optimal in Deep Regularized ResNets and Transformers.” 39th Conference on Neural Information Processing Systems, vol. 38, Neural Information Processing Systems Foundation, 2025, pp. 48646–77, doi:10.52202/085713-1450. short: P. Súkeník, C. Lampert, M. Mondelli, in:, 39th Conference on Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2025, pp. 48646–48677. conference: end_date: 2025-12-07 location: San Diego, CA, United States name: 'NeurIPS: Neural Information Processing Systems' start_date: 2025-12-02 corr_author: '1' das_tickbox: '0' date_created: 2026-09-06T22:01:59Z date_published: 2025-12-02T00:00:00Z date_updated: 2026-09-10T08:11:46Z day: '02' ddc: - '000' department: - _id: MaMo - _id: GradSch - _id: ChLa doi: 10.52202/085713-1450 external_id: arxiv: - '2505.15239' fulldoi: https://doi.org/10.52202/085713-1450 intvolume: ' 38' language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.52202/085713-1450 month: '12' oa: 1 oa_version: Published Version page: 48646-48677 project: - _id: 911e6d1f-16d5-11f0-9cad-c5c68c6a1cdf grant_number: '101161364' name: 'Inference in High Dimensions: Light-speed Algorithms and Information Limits' publication: 39th Conference on Neural Information Processing Systems publication_identifier: isbn: - '9798331338275' issn: - 1049-5258 publication_status: published publisher: Neural Information Processing Systems Foundation quality_controlled: '1' researchdata_availability: no scopus_import: '1' status: public supplementarymaterial: no title: Neural collapse is globally optimal in deep regularized ResNets and transformers type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 38 year: '2025' ... --- OA_place: publisher OA_type: free access _id: '22824' abstract: - lang: eng text: "We present new fast-rate PAC-Bayesian generalization bounds for multi-task and\r\nmeta-learning in the unbalanced setting, i.e. when the tasks have training sets of\r\ndifferent sizes, as is typically the case in real-world scenarios. Previously, only\r\nstandard-rate bounds were known for this situation, while fast-rate bounds were\r\nlimited to the setting where all training sets are of equal size. Our new bounds\r\nare numerically computable as well as interpretable, and we demonstrate their\r\nflexibility in handling a number of cases where they give stronger guarantees\r\nthan previous bounds. Besides the bounds themselves, we also make conceptual\r\ncontributions: we demonstrate that the unbalanced multi-task setting has different\r\nstatistical properties than the balanced situation, specifically that proofs from\r\nthe balanced situation do not carry over to the unbalanced setting. Additionally,\r\nwe shed light on the fact that the unbalanced situation allows two meaningful\r\ndefinitions of multi-task risk, depending on whether all tasks should be considered\r\nequally important or if sample-rich tasks should receive more weight than samplepoor ones." acknowledged_ssus: - _id: ScienComp acknowledgement: This research was supported by the Scientific Service Units (SSU) of ISTA through resources provided by Scientific Computing (SciComp). alternative_title: - Advances in Neural Information Processing Systems article_processing_charge: No author: - first_name: Hossein full_name: Zakerinia, Hossein id: 653bd8b6-f394-11eb-9cf6-c0bbf6cd78d4 last_name: Zakerinia orcid: 0009-0007-3977-6462 - first_name: Christoph full_name: Lampert, Christoph id: 40C20FD2-F248-11E8-B48F-1D18A9856A87 last_name: Lampert orcid: 0000-0001-8622-7887 citation: ama: 'Zakerinia H, Lampert C. Fast rate bounds for multi-task and meta-learning with different sample sizes. In: 39th Conference on Neural Information Processing Systems. Vol 38. Neural Information Processing Systems Foundation; 2025:9062-9093. doi:10.52202/085713-0278' apa: 'Zakerinia, H., & Lampert, C. (2025). Fast rate bounds for multi-task and meta-learning with different sample sizes. In 39th Conference on Neural Information Processing Systems (Vol. 38, pp. 9062–9093). San Diego, CA, United States: Neural Information Processing Systems Foundation. https://doi.org/10.52202/085713-0278' chicago: Zakerinia, Hossein, and Christoph Lampert. “Fast Rate Bounds for Multi-Task and Meta-Learning with Different Sample Sizes.” In 39th Conference on Neural Information Processing Systems, 38:9062–93. Neural Information Processing Systems Foundation, 2025. https://doi.org/10.52202/085713-0278. ieee: H. Zakerinia and C. Lampert, “Fast rate bounds for multi-task and meta-learning with different sample sizes,” in 39th Conference on Neural Information Processing Systems, San Diego, CA, United States, 2025, vol. 38, pp. 9062–9093. ista: 'Zakerinia H, Lampert C. 2025. Fast rate bounds for multi-task and meta-learning with different sample sizes. 39th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems, Advances in Neural Information Processing Systems, vol. 38, 9062–9093.' mla: Zakerinia, Hossein, and Christoph Lampert. “Fast Rate Bounds for Multi-Task and Meta-Learning with Different Sample Sizes.” 39th Conference on Neural Information Processing Systems, vol. 38, Neural Information Processing Systems Foundation, 2025, pp. 9062–93, doi:10.52202/085713-0278. short: H. Zakerinia, C. Lampert, in:, 39th Conference on Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2025, pp. 9062–9093. conference: end_date: 2025-12-07 location: San Diego, CA, United States name: 'NeurIPS: Neural Information Processing Systems' start_date: 2025-12-02 corr_author: '1' das_tickbox: '0' date_created: 2026-09-06T22:01:59Z date_published: 2025-12-02T00:00:00Z date_updated: 2026-09-10T08:37:33Z day: '02' department: - _id: GradSch - _id: ChLa doi: 10.52202/085713-0278 fulldoi: https://doi.org/10.52202/085713-0278 intvolume: ' 38' language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.52202/085713-0278 month: '12' oa: 1 oa_version: Published Version page: 9062-9093 publication: 39th Conference on Neural Information Processing Systems publication_identifier: isbn: - '9798331338275' issn: - 1049-5258 publication_status: published publisher: Neural Information Processing Systems Foundation quality_controlled: '1' researchdata_availability: no scopus_import: '1' status: public supplementarymaterial: yes title: Fast rate bounds for multi-task and meta-learning with different sample sizes type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 38 year: '2025' ... --- OA_place: publisher OA_type: diamond _id: '20299' abstract: - lang: eng text: "Deterministic Markov Decision Processes (DMDPs) are a mathematical framework for decision-making where the outcomes and future possible actions are deterministically determined by the current action taken. DMDPs can be viewed as a finite directed weighted graph, where in each step, the controller chooses an outgoing edge. An objective is a measurable function on runs (or infinite trajectories) of the DMDP, and the value for an objective is the maximal cumulative reward (or weight) that the controller can guarantee. We consider the classical mean-payoff (aka limit-average) objective, which is a basic and fundamental objective.\r\n\r\nHoward's policy iteration algorithm is a popular method for solving DMDPs with mean-payoff objectives. Although Howard's algorithm performs well in practice, as experimental studies suggested, the best known upper bound is exponential and the current known lower bound is as follows: For the input size I, the algorithm requires (math formular) iterations, where (math formular) hides the poly-logarithmic factors, i.e., the current lower bound on iterations is sub-linear with respect to the input size. Our main result is an improved lower bound for this fundamental algorithm where we show that for the input size I, the algorithm requires (math formular) iterations." acknowledgement: "This research was partially supported by the ERC CoG 863818 (ForM-SMArt) grant and Austrian Science Fund (FWF) 10.55776/COE12.\r\n" alternative_title: - PMLR article_processing_charge: No 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: Jakob full_name: De Raaij, Jakob last_name: De Raaij citation: ama: 'Asadi A, Chatterjee K, De Raaij J. Lower bound on Howard policy iteration for deterministic Markov Decision Processes. In: The 41st Conference on Uncertainty in Artificial Intelligence. Vol 286. ML Research Press; 2025:223-232.' apa: 'Asadi, A., Chatterjee, K., & De Raaij, J. (2025). Lower bound on Howard policy iteration for deterministic Markov Decision Processes. In The 41st Conference on Uncertainty in Artificial Intelligence (Vol. 286, pp. 223–232). Rio de Janeiro, Brazil: ML Research Press.' chicago: Asadi, Ali, Krishnendu Chatterjee, and Jakob De Raaij. “Lower Bound on Howard Policy Iteration for Deterministic Markov Decision Processes.” In The 41st Conference on Uncertainty in Artificial Intelligence, 286:223–32. ML Research Press, 2025. ieee: A. Asadi, K. Chatterjee, and J. De Raaij, “Lower bound on Howard policy iteration for deterministic Markov Decision Processes,” in The 41st Conference on Uncertainty in Artificial Intelligence, Rio de Janeiro, Brazil, 2025, vol. 286, pp. 223–232. ista: 'Asadi A, Chatterjee K, De Raaij J. 2025. Lower bound on Howard policy iteration for deterministic Markov Decision Processes. The 41st Conference on Uncertainty in Artificial Intelligence. UAI: Conference on Uncertainty in Artificial Intelligence, PMLR, vol. 286, 223–232.' mla: Asadi, Ali, et al. “Lower Bound on Howard Policy Iteration for Deterministic Markov Decision Processes.” The 41st Conference on Uncertainty in Artificial Intelligence, vol. 286, ML Research Press, 2025, pp. 223–32. short: A. Asadi, K. Chatterjee, J. De Raaij, in:, The 41st Conference on Uncertainty in Artificial Intelligence, ML Research Press, 2025, pp. 223–232. conference: end_date: 2025-07-25 location: Rio de Janeiro, Brazil name: 'UAI: Conference on Uncertainty in Artificial Intelligence' start_date: 2025-07-21 corr_author: '1' date_created: 2025-09-07T22:01:34Z date_published: 2025-01-01T00:00:00Z date_updated: 2026-09-16T07:01:05Z day: '01' ddc: - '000' department: - _id: KrCh - _id: GradSch ec_funded: 1 external_id: arxiv: - '2506.12254' file: - access_level: open_access checksum: 4180c81bb6ed3b4f5c7a8e48d06520c6 content_type: application/pdf creator: dernst date_created: 2025-09-09T06:27:59Z date_updated: 2025-09-09T06:27:59Z file_id: '20313' file_name: 2025_UAI_Asadi.pdf file_size: 317097 relation: main_file success: 1 file_date_updated: 2025-09-09T06:27:59Z has_accepted_license: '1' intvolume: ' 286' language: - iso: eng month: '01' oa: 1 oa_version: Published Version page: 223-232 project: - _id: 0599E47C-7A3F-11EA-A408-12923DDC885E call_identifier: H2020 grant_number: '863818' name: 'Formal Methods for Stochastic Models: Algorithms and Applications' - _id: 4029cfc7-b034-11f1-9e55-88ab2ff3b6ee grant_number: COE12 name: Bilateral Artificial Intelligence (Chatterjee) publication: The 41st Conference on Uncertainty in Artificial Intelligence publication_identifier: eissn: - 2640-3498 publication_status: published publisher: ML Research Press quality_controlled: '1' scopus_import: '1' status: public title: Lower bound on Howard policy iteration for deterministic Markov Decision Processes tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 286 year: '2025' ... --- OA_place: publisher OA_type: diamond _id: '20297' abstract: - lang: eng text: "A standard model that arises in several applications in sequential decision-making is partially observable Markov decision processes (POMDPs) where a decision-making agent interacts with an uncertain environment. A basic objective in POMDPs is the reachability objective, where given a target set of states, the goal is to eventually arrive at one of them.\r\n\r\nThe limit-sure problem asks whether reachability can be ensured with probability arbitrarily close to 1. In general, the limit-sure reachability problem for POMDPs is undecidable. However, in many practical cases, the most relevant question is the existence of policies with a small amount of memory. In this work, we study the limit-sure reachability problem for POMDPs with a fixed amount of memory. We establish that the computational complexity of the problem is NP-complete." acknowledgement: This research was partially supported by Austrian Science Fund (FWF) 10.55776/COE12, the support of the French Agence Nationale de la Recherche (ANR) under reference ANR-21-CE40-0020 (CONVERGENCE project), and the ERC CoG 863818 (ForM-SMArt) grant. alternative_title: - PMLR article_processing_charge: No 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: Raimundo J full_name: Saona Urmeneta, Raimundo J id: BD1DF4C4-D767-11E9-B658-BC13E6697425 last_name: Saona Urmeneta orcid: 0000-0001-5103-038X - first_name: Ali full_name: Shafiee, Ali id: 2783031a-7378-11f0-b2d0-f17f1db2ebad last_name: Shafiee citation: ama: 'Asadi A, Chatterjee K, Saona Urmeneta RJ, Shafiee A. Limit-sure reachability for small memory policies in POMDPs is NP-complete. In: The 41st Conference on Uncertainty in Artificial Intelligence. Vol 286. ML Research Press; 2025:238-247.' apa: 'Asadi, A., Chatterjee, K., Saona Urmeneta, R. J., & Shafiee, A. (2025). Limit-sure reachability for small memory policies in POMDPs is NP-complete. In The 41st Conference on Uncertainty in Artificial Intelligence (Vol. 286, pp. 238–247). Rio de Janeiro, Brazil: ML Research Press.' chicago: Asadi, Ali, Krishnendu Chatterjee, Raimundo J Saona Urmeneta, and Ali Shafiee. “Limit-Sure Reachability for Small Memory Policies in POMDPs Is NP-Complete.” In The 41st Conference on Uncertainty in Artificial Intelligence, 286:238–47. ML Research Press, 2025. ieee: A. Asadi, K. Chatterjee, R. J. Saona Urmeneta, and A. Shafiee, “Limit-sure reachability for small memory policies in POMDPs is NP-complete,” in The 41st Conference on Uncertainty in Artificial Intelligence, Rio de Janeiro, Brazil, 2025, vol. 286, pp. 238–247. ista: 'Asadi A, Chatterjee K, Saona Urmeneta RJ, Shafiee A. 2025. Limit-sure reachability for small memory policies in POMDPs is NP-complete. The 41st Conference on Uncertainty in Artificial Intelligence. UAI: Conference on Uncertainty in Artificial Intelligence, PMLR, vol. 286, 238–247.' mla: Asadi, Ali, et al. “Limit-Sure Reachability for Small Memory Policies in POMDPs Is NP-Complete.” The 41st Conference on Uncertainty in Artificial Intelligence, vol. 286, ML Research Press, 2025, pp. 238–47. short: A. Asadi, K. Chatterjee, R.J. Saona Urmeneta, A. Shafiee, in:, The 41st Conference on Uncertainty in Artificial Intelligence, ML Research Press, 2025, pp. 238–247. conference: end_date: 2025-07-25 location: Rio de Janeiro, Brazil name: 'UAI: Conference on Uncertainty in Artificial Intelligence' start_date: 2025-07-21 corr_author: '1' date_created: 2025-09-07T22:01:34Z date_published: 2025-07-01T00:00:00Z date_updated: 2026-09-16T07:03:02Z day: '01' ddc: - '000' department: - _id: KrCh - _id: GradSch ec_funded: 1 external_id: arxiv: - '2412.00941' file: - access_level: open_access checksum: 1a37ebe7ba73ab6985765bf0d17a0acc content_type: application/pdf creator: dernst date_created: 2025-09-09T08:19:41Z date_updated: 2025-09-09T08:19:41Z file_id: '20315' file_name: 2025_UAI_AsadiAli.pdf file_size: 307458 relation: main_file success: 1 file_date_updated: 2025-09-09T08:19:41Z has_accepted_license: '1' intvolume: ' 286' language: - iso: eng month: '07' oa: 1 oa_version: Published Version page: 238-247 project: - _id: 0599E47C-7A3F-11EA-A408-12923DDC885E call_identifier: H2020 grant_number: '863818' name: 'Formal Methods for Stochastic Models: Algorithms and Applications' - _id: 4029cfc7-b034-11f1-9e55-88ab2ff3b6ee grant_number: COE12 name: Bilateral Artificial Intelligence (Chatterjee) publication: The 41st Conference on Uncertainty in Artificial Intelligence publication_identifier: eissn: - 2640-3498 publication_status: published publisher: ML Research Press quality_controlled: '1' scopus_import: '1' status: public title: Limit-sure reachability for small memory policies in POMDPs is NP-complete 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: 286 year: '2025' ... --- APC_amount: 3599,50 EUR DOAJ_listed: '1' OA_place: publisher OA_type: gold PlanS_conform: '1' _id: '20646' abstract: - lang: eng text: Describing general quantum many-body dynamics is a challenging task due to the exponential growth of the Hilbert space with system size. The time-dependent variational principle (TDVP) provides a powerful tool to tackle this task by projecting quantum evolution onto a classical dynamical system within a variational manifold. In classical systems, periodic orbits play a crucial role in understanding the structure of the phase space and the long-term behavior of the system. However, finding periodic orbits is generally difficult, and their existence and properties in generic TDVP dynamics over matrix product states have remained largely unexplored. In this work, we develop an algorithm to systematically identify and characterize periodic orbits in TDVP dynamics. Applying our method to the periodically kicked Ising model, we uncover both stable and unstable periodic orbits. We characterize the Kolmogorov-Arnold-Moser tori in the vicinity of stable periodic orbits and track the change of the periodic orbits as we modify the Hamiltonian parameters. We observe that periodic orbits exist at any value of the coupling constant of the kicked Ising model between prethermal and fully thermalizing regimes, but their relevance to quantum dynamics and imprint on quantum eigenstates diminishes as the system leaves the prethermal regime. Our results demonstrate that periodic orbits provide valuable insights into the TDVP approximation of quantum many-body evolution and establish a closer connection between quantum and classical chaos. acknowledgement: We acknowledge useful discussions with C. Kollath, A. Green, and D. Huse. E.P., M.L., and M.S. acknowledge support by the European Research Council under the European Union’s Horizon 2020 research and innovation program (Grant Agreement No. 850899). This research was funded in whole or in part by the Austrian Science Fund (FWF) (Grant No. 10.55776/COE1). For open access purposes, the author has applied a CC BY public copyright license to any author accepted manuscript version arising from this submission. M.L. acknowledges support by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy—EXC-2111—390814868. This research was supported in part by National Science Foundation (NSF) Grant No. PHY-2309135 to the Kavli Institute for Theoretical Physics (KITP) and by the Erwin Schrödinger International Institute for Mathematics and Physics (ESI). article_number: '040333' article_processing_charge: Yes article_type: original arxiv: 1 author: - first_name: Elena full_name: Petrova, Elena id: 0ac84990-897b-11ed-a09c-f5abb56a4ede last_name: Petrova - first_name: Marko full_name: Ljubotina, Marko id: F75EE9BE-5C90-11EA-905D-16643DDC885E last_name: Ljubotina orcid: 0000-0003-0038-7068 - first_name: Gökhan full_name: Yalniz, Gökhan id: 66E74FA2-D8BF-11E9-8249-8DE2E5697425 last_name: Yalniz orcid: 0000-0002-8490-9312 - first_name: Maksym full_name: Serbyn, Maksym id: 47809E7E-F248-11E8-B48F-1D18A9856A87 last_name: Serbyn orcid: 0000-0002-2399-5827 citation: ama: Petrova E, Ljubotina M, Yalniz G, Serbyn M. Finding periodic orbits in projected quantum many-body dynamics. PRX Quantum. 2025;6(4). doi:10.1103/tldp-kvkd apa: Petrova, E., Ljubotina, M., Yalniz, G., & Serbyn, M. (2025). Finding periodic orbits in projected quantum many-body dynamics. PRX Quantum. American Physical Society. https://doi.org/10.1103/tldp-kvkd chicago: Petrova, Elena, Marko Ljubotina, Gökhan Yalniz, and Maksym Serbyn. “Finding Periodic Orbits in Projected Quantum Many-Body Dynamics.” PRX Quantum. American Physical Society, 2025. https://doi.org/10.1103/tldp-kvkd. ieee: E. Petrova, M. Ljubotina, G. Yalniz, and M. Serbyn, “Finding periodic orbits in projected quantum many-body dynamics,” PRX Quantum, vol. 6, no. 4. American Physical Society, 2025. ista: Petrova E, Ljubotina M, Yalniz G, Serbyn M. 2025. Finding periodic orbits in projected quantum many-body dynamics. PRX Quantum. 6(4), 040333. mla: Petrova, Elena, et al. “Finding Periodic Orbits in Projected Quantum Many-Body Dynamics.” PRX Quantum, vol. 6, no. 4, 040333, American Physical Society, 2025, doi:10.1103/tldp-kvkd. short: E. Petrova, M. Ljubotina, G. Yalniz, M. Serbyn, PRX Quantum 6 (2025). corr_author: '1' date_created: 2025-11-14T09:40:52Z date_published: 2025-11-12T00:00:00Z date_updated: 2026-09-16T07:04:35Z day: '12' ddc: - '539' department: - _id: GradSch - _id: BjHo - _id: MaSe doi: 10.1103/tldp-kvkd ec_funded: 1 external_id: arxiv: - '2504.12472' isi: - '001616473700003' file: - access_level: open_access checksum: 5d6d04ac518b4118405334e1ddc7a56d content_type: application/pdf creator: gyalniz date_created: 2025-11-14T09:44:10Z date_updated: 2025-11-14T09:44:10Z file_id: '20647' file_name: tldp-kvkd.pdf file_size: 2504713 relation: main_file success: 1 file_date_updated: 2025-11-14T09:44:10Z fulldoi: https://doi.org/10.1103/tldp-kvkd has_accepted_license: '1' intvolume: ' 6' isi: 1 issue: '4' language: - iso: eng month: '11' oa: 1 oa_version: Published Version project: - _id: 23841C26-32DE-11EA-91FC-C7463DDC885E call_identifier: H2020 grant_number: '850899' name: 'Non-Ergodic Quantum Matter: Universality, Dynamics and Control' - _id: 3AC91DDA-15DF-11EA-824D-93A3E7B544D1 call_identifier: FWF name: FWF Open Access Fund - _id: 92c64506-16d5-11f0-9cad-87ce313ee832 grant_number: COE01 name: Quantum Science Austria (Serbyn) publication: PRX Quantum publication_identifier: eissn: - 2691-3399 publication_status: published publisher: American Physical Society quality_controlled: '1' related_material: link: - description: News on ISTA website relation: press_release url: https://ista.ac.at/en/news/reaching-for-the-quantum-scars/ scopus_import: '1' status: public title: Finding periodic orbits in projected quantum many-body dynamics 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: '2025' ... --- OA_place: publisher OA_type: free access _id: '22828' abstract: - lang: eng text: 'We propose Joint Moment Estimation (JME), a method for continually and privately estimating both the first and second moments of a data stream with reduced noise compared to naive approaches. JME supports the matrix mechanism and exploits a joint sensitivity analysis to identify a privacy regime in which the second-moment estimation incurs no additional privacy cost, thereby improving accuracy while maintaining privacy. We demonstrate JME’s effectiveness in two applications: estimating the running mean and covariance matrix for Gaussian density estimation and model training with DP-Adam.' acknowledgement: "We thank Monika Henzinger for her valuable feedback and insightful discussions on earlier versions\r\nof this draft. We are also grateful to Mher Safaryan for his contributions to discussions on DP-Adam.\r\nAdditionally, we thank Ryan McKenna for suggesting Joint Clipping as a baseline.\r\nJalaj Upadhyay’s research was funded by the Rutgers Decanal Grant no. 302918, NSF CNS 2433628,\r\nGoogle Research Scholar Award, and Google Seed Fund Grant. A part of this work was done while\r\nvisiting the Institute of Science and Technology Austria (ISTA).\r\nNikita Kalinin’s research was funded in part by the Austrian Science Fund (FWF) [10.55776/COE12]" alternative_title: - Advances in Neural Information Processing Systems article_processing_charge: No author: - first_name: Nikita full_name: Kalinin, Nikita id: 4b14526e-14d2-11ed-ba64-c14c9553d137 last_name: Kalinin - first_name: Jalaj full_name: Upadhyay, Jalaj last_name: Upadhyay - first_name: Christoph full_name: Lampert, Christoph id: 40C20FD2-F248-11E8-B48F-1D18A9856A87 last_name: Lampert orcid: 0000-0001-8622-7887 citation: ama: 'Kalinin N, Upadhyay J, Lampert C. Continual release moment estimation with differential privacy. In: Advances in Neural Information Processing Systems. Vol 38. Neural Information Processing Systems Foundation; 2025:64002-64047. doi:10.52202/085713-1924' apa: 'Kalinin, N., Upadhyay, J., & Lampert, C. (2025). Continual release moment estimation with differential privacy. In Advances in Neural Information Processing Systems (Vol. 38, pp. 64002–64047). San Diego, CA, United States: Neural Information Processing Systems Foundation. https://doi.org/10.52202/085713-1924' chicago: Kalinin, Nikita, Jalaj Upadhyay, and Christoph Lampert. “Continual Release Moment Estimation with Differential Privacy.” In Advances in Neural Information Processing Systems, 38:64002–47. Neural Information Processing Systems Foundation, 2025. https://doi.org/10.52202/085713-1924. ieee: N. Kalinin, J. Upadhyay, and C. Lampert, “Continual release moment estimation with differential privacy,” in Advances in Neural Information Processing Systems, San Diego, CA, United States, 2025, vol. 38, pp. 64002–64047. ista: 'Kalinin N, Upadhyay J, Lampert C. 2025. Continual release moment estimation with differential privacy. Advances in Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems, Advances in Neural Information Processing Systems, vol. 38, 64002–64047.' mla: Kalinin, Nikita, et al. “Continual Release Moment Estimation with Differential Privacy.” Advances in Neural Information Processing Systems, vol. 38, Neural Information Processing Systems Foundation, 2025, pp. 64002–47, doi:10.52202/085713-1924. short: N. Kalinin, J. Upadhyay, C. Lampert, in:, Advances in Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2025, pp. 64002–64047. conference: location: San Diego, CA, United States name: 'NeurIPS: Neural Information Processing Systems' corr_author: '1' das_tickbox: '0' date_created: 2026-09-06T22:02:00Z date_published: 2025-12-02T00:00:00Z date_updated: 2026-09-16T07:40:56Z day: '02' department: - _id: GradSch - _id: ChLa doi: 10.52202/085713-1924 fulldoi: https://doi.org/10.52202/085713-1924 intvolume: ' 38' language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.52202/085713-1924 month: '12' oa: 1 oa_version: Published Version page: 64002-64047 project: - _id: d8f03aaa-b035-11f1-8588-d5147fa879e0 grant_number: COE12 name: Bilateral Artificial Intelligence (Lampert) publication: Advances in Neural Information Processing Systems publication_identifier: isbn: - '9798331338275' issn: - 1049-5258 publication_status: published publisher: Neural Information Processing Systems Foundation quality_controlled: '1' researchdata_availability: no scopus_import: '1' status: public supplementarymaterial: no title: Continual release moment estimation with differential privacy type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 38 year: '2025' ... --- OA_place: repository OA_type: green _id: '22827' abstract: - lang: eng text: Quantized training of Large Language Models (LLMs) remains an open challenge, as maintaining accuracy while performing all matrix multiplications in low precision has proven difficult. This is particularly the case when fine-tuning pre-trained models, which can have large weight, activation, and error (output gradient) outlier values that make lower-precision optimization difficult. To address this, we present HALO, a new quantization-aware training approach for Transformers that enables accurate and efficient low-precision training by combining 1) strategic placement of Hadamard rotations in both forward and backward passes, which mitigate outliers, 2) high-performance kernel support, and 3) FSDP integration for low-precision communication. Our approach ensures that all large matrix multiplications during the forward and backward passes are executed in lower precision. Applied to LLaMa models, HALO achieves near-full-precision-equivalent results during fine-tuning on various tasks, while delivering up to 1.41x end-to-end speedup for full fine-tuning on RTX 4090 GPUs. HALO efficiently supports both standard and parameter-efficient fine-tuning (PEFT). Our results demonstrate the first practical approach to fully quantized LLM fine-tuning that maintains accuracy in INT8 and FP6 precision, while delivering performance benefits. acknowledgement: "This project has received funding from the European Research Council (ERC) under the European\r\nUnion’s Horizon 2020 program (grant agreement PSAP, No. 101002047. This research also obtained\r\nfunding from the “UrbanTwin: An urban digital twin for climate action: Assessing policies and\r\nsolutions for energy, water and infrastructure” project, funded by the ETH-Domain Joint Initiative\r\nprogram in the Strategic Area Energy, Climate and Sustainable Environment." alternative_title: - Advances in Neural Information Processing Systems article_processing_charge: No arxiv: 1 author: - first_name: Saleh full_name: Ashkboos, Saleh last_name: Ashkboos - first_name: Mahdi full_name: Nikdan, Mahdi id: 66374281-f394-11eb-9cf6-869147deecc0 last_name: Nikdan - first_name: Soroush full_name: Tabesh, Soroush id: 06000900-6068-11ef-8d61-c2472ef2e752 last_name: Tabesh orcid: 0009-0003-4119-6281 - first_name: Roberto full_name: Lopez Castro, Roberto id: 18495c31-fb57-11ef-ba0d-c290e10e394e last_name: Lopez Castro - first_name: Torsten full_name: Hoefler, Torsten last_name: Hoefler - first_name: Dan-Adrian full_name: Alistarh, Dan-Adrian id: 4A899BFC-F248-11E8-B48F-1D18A9856A87 last_name: Alistarh orcid: 0000-0003-3650-940X citation: ama: 'Ashkboos S, Nikdan M, Tabesh S, Lopez Castro R, Hoefler T, Alistarh D-A. HALO: Hadamard-assisted lower-precision optimization for LLMs. In: 39th Conference on Neural Information Processing Systems. Vol 38. Neural Information Processing Systems Foundation; 2025:131755-131780. doi:10.52202/085713-3966' apa: 'Ashkboos, S., Nikdan, M., Tabesh, S., Lopez Castro, R., Hoefler, T., & Alistarh, D.-A. (2025). HALO: Hadamard-assisted lower-precision optimization for LLMs. In 39th Conference on Neural Information Processing Systems (Vol. 38, pp. 131755–131780). San Diego, CA, United States: Neural Information Processing Systems Foundation. https://doi.org/10.52202/085713-3966' chicago: 'Ashkboos, Saleh, Mahdi Nikdan, Soroush Tabesh, Roberto Lopez Castro, Torsten Hoefler, and Dan-Adrian Alistarh. “HALO: Hadamard-Assisted Lower-Precision Optimization for LLMs.” In 39th Conference on Neural Information Processing Systems, 38:131755–80. Neural Information Processing Systems Foundation, 2025. https://doi.org/10.52202/085713-3966.' ieee: 'S. Ashkboos, M. Nikdan, S. Tabesh, R. Lopez Castro, T. Hoefler, and D.-A. Alistarh, “HALO: Hadamard-assisted lower-precision optimization for LLMs,” in 39th Conference on Neural Information Processing Systems, San Diego, CA, United States, 2025, vol. 38, pp. 131755–131780.' ista: 'Ashkboos S, Nikdan M, Tabesh S, Lopez Castro R, Hoefler T, Alistarh D-A. 2025. HALO: Hadamard-assisted lower-precision optimization for LLMs. 39th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems, Advances in Neural Information Processing Systems, vol. 38, 131755–131780.' mla: 'Ashkboos, Saleh, et al. “HALO: Hadamard-Assisted Lower-Precision Optimization for LLMs.” 39th Conference on Neural Information Processing Systems, vol. 38, Neural Information Processing Systems Foundation, 2025, pp. 131755–80, doi:10.52202/085713-3966.' short: S. Ashkboos, M. Nikdan, S. Tabesh, R. Lopez Castro, T. Hoefler, D.-A. Alistarh, in:, 39th Conference on Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2025, pp. 131755–131780. conference: end_date: 2025-12-07 location: San Diego, CA, United States name: 'NeurIPS: Neural Information Processing Systems' start_date: 2025-12-02 das_tickbox: '0' date_created: 2026-09-06T22:02:00Z date_published: 2025-12-01T00:00:00Z date_updated: 2026-09-17T06:39:18Z day: '01' department: - _id: DaAl - _id: GradSch doi: 10.52202/085713-3966 external_id: arxiv: - '2501.02625' fulldoi: https://doi.org/10.52202/085713-3966 intvolume: ' 38' language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.48550/arXiv.2501.02625 month: '12' oa: 1 oa_version: Preprint page: 131755-131780 publication: 39th Conference on Neural Information Processing Systems publication_identifier: eissn: - 1049-5258 isbn: - '9798331338275' publication_status: published publisher: Neural Information Processing Systems Foundation quality_controlled: '1' researchdata_availability: no scopus_import: '1' status: public supplementarymaterial: no title: 'HALO: Hadamard-assisted lower-precision optimization for LLMs' type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 38 year: '2025' ...