--- _id: '13142' abstract: - lang: eng text: Reinforcement learning has received much attention for learning controllers of deterministic systems. We consider a learner-verifier framework for stochastic control systems and survey recent methods that formally guarantee a conjunction of reachability and safety properties. Given a property and a lower bound on the probability of the property being satisfied, our framework jointly learns a control policy and a formal certificate to ensure the satisfaction of the property with a desired probability threshold. Both the control policy and the formal certificate are continuous functions from states to reals, which are learned as parameterized neural networks. While in the deterministic case, the certificates are invariant and barrier functions for safety, or Lyapunov and ranking functions for liveness, in the stochastic case the certificates are supermartingales. For certificate verification, we use interval arithmetic abstract interpretation to bound the expected values of neural network functions. acknowledgement: This work was supported in part by the ERC-2020-AdG 101020093, ERC CoG 863818 (FoRM-SMArt) and the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 665385. alternative_title: - LNCS article_processing_charge: No author: - first_name: Krishnendu full_name: Chatterjee, Krishnendu id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87 last_name: Chatterjee orcid: 0000-0002-4561-241X - 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: Mathias full_name: Lechner, Mathias id: 3DC22916-F248-11E8-B48F-1D18A9856A87 last_name: Lechner - first_name: Dorde full_name: Zikelic, Dorde id: 294AA7A6-F248-11E8-B48F-1D18A9856A87 last_name: Zikelic citation: ama: 'Chatterjee K, Henzinger TA, Lechner M, Zikelic D. A learner-verifier framework for neural network controllers and certificates of stochastic systems. In: Tools and Algorithms for the Construction and Analysis of Systems . Vol 13993. Springer Nature; 2023:3-25. doi:10.1007/978-3-031-30823-9_1' apa: 'Chatterjee, K., Henzinger, T. A., Lechner, M., & Zikelic, D. (2023). A learner-verifier framework for neural network controllers and certificates of stochastic systems. In Tools and Algorithms for the Construction and Analysis of Systems (Vol. 13993, pp. 3–25). Paris, France: Springer Nature. https://doi.org/10.1007/978-3-031-30823-9_1' chicago: Chatterjee, Krishnendu, Thomas A Henzinger, Mathias Lechner, and Dorde Zikelic. “A Learner-Verifier Framework for Neural Network Controllers and Certificates of Stochastic Systems.” In Tools and Algorithms for the Construction and Analysis of Systems , 13993:3–25. Springer Nature, 2023. https://doi.org/10.1007/978-3-031-30823-9_1. ieee: K. Chatterjee, T. A. Henzinger, M. Lechner, and D. Zikelic, “A learner-verifier framework for neural network controllers and certificates of stochastic systems,” in Tools and Algorithms for the Construction and Analysis of Systems , Paris, France, 2023, vol. 13993, pp. 3–25. ista: 'Chatterjee K, Henzinger TA, Lechner M, Zikelic D. 2023. A learner-verifier framework for neural network controllers and certificates of stochastic systems. Tools and Algorithms for the Construction and Analysis of Systems . TACAS: Tools and Algorithms for the Construction and Analysis of Systems, LNCS, vol. 13993, 3–25.' mla: Chatterjee, Krishnendu, et al. “A Learner-Verifier Framework for Neural Network Controllers and Certificates of Stochastic Systems.” Tools and Algorithms for the Construction and Analysis of Systems , vol. 13993, Springer Nature, 2023, pp. 3–25, doi:10.1007/978-3-031-30823-9_1. short: K. Chatterjee, T.A. Henzinger, M. Lechner, D. Zikelic, in:, Tools and Algorithms for the Construction and Analysis of Systems , Springer Nature, 2023, pp. 3–25. conference: end_date: 2023-04-27 location: Paris, France name: 'TACAS: Tools and Algorithms for the Construction and Analysis of Systems' start_date: 2023-04-22 date_created: 2023-06-18T22:00:47Z date_published: 2023-04-22T00:00:00Z date_updated: 2023-06-19T08:30:54Z day: '22' ddc: - '000' department: - _id: KrCh - _id: ToHe doi: 10.1007/978-3-031-30823-9_1 ec_funded: 1 file: - access_level: open_access checksum: 3d8a8bb24d211bc83360dfc2fd744307 content_type: application/pdf creator: dernst date_created: 2023-06-19T08:29:30Z date_updated: 2023-06-19T08:29:30Z file_id: '13150' file_name: 2023_LNCS_Chatterjee.pdf file_size: 528455 relation: main_file success: 1 file_date_updated: 2023-06-19T08:29:30Z has_accepted_license: '1' intvolume: ' 13993' language: - iso: eng license: https://creativecommons.org/licenses/by/4.0/ month: '04' oa: 1 oa_version: Published Version page: 3-25 project: - _id: 0599E47C-7A3F-11EA-A408-12923DDC885E call_identifier: H2020 grant_number: '863818' name: 'Formal Methods for Stochastic Models: Algorithms and Applications' - _id: 2564DBCA-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '665385' name: International IST Doctoral Program publication: 'Tools and Algorithms for the Construction and Analysis of Systems ' publication_identifier: eissn: - 1611-3349 isbn: - '9783031308222' issn: - 0302-9743 publication_status: published publisher: Springer Nature quality_controlled: '1' scopus_import: '1' status: public title: A learner-verifier framework for neural network controllers and certificates of stochastic systems 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: 13993 year: '2023' ... --- _id: '13141' abstract: - lang: eng text: "We automatically compute a new class of environment assumptions in two-player turn-based finite graph games which characterize an “adequate cooperation” needed from the environment to allow the system player to win. Given an ω-regular winning condition Φ for the system player, we compute an ω-regular assumption Ψ for the environment player, such that (i) every environment strategy compliant with Ψ allows the system to fulfill Φ (sufficiency), (ii) Ψ\r\n can be fulfilled by the environment for every strategy of the system (implementability), and (iii) Ψ does not prevent any cooperative strategy choice (permissiveness).\r\nFor parity games, which are canonical representations of ω-regular games, we present a polynomial-time algorithm for the symbolic computation of adequately permissive assumptions and show that our algorithm runs faster and produces better assumptions than existing approaches—both theoretically and empirically. To the best of our knowledge, for ω\r\n-regular games, we provide the first algorithm to compute sufficient and implementable environment assumptions that are also permissive." alternative_title: - LNCS article_processing_charge: No author: - first_name: Ashwani full_name: Anand, Ashwani last_name: Anand - first_name: Kaushik full_name: Mallik, Kaushik id: 0834ff3c-6d72-11ec-94e0-b5b0a4fb8598 last_name: Mallik orcid: 0000-0001-9864-7475 - first_name: Satya Prakash full_name: Nayak, Satya Prakash last_name: Nayak - first_name: Anne Kathrin full_name: Schmuck, Anne Kathrin last_name: Schmuck citation: ama: 'Anand A, Mallik K, Nayak SP, Schmuck AK. Computing adequately permissive assumptions for synthesis. In: TACAS 2023: Tools and Algorithms for the Construction and Analysis of Systems. Vol 13994. Springer Nature; 2023:211-228. doi:10.1007/978-3-031-30820-8_15' apa: 'Anand, A., Mallik, K., Nayak, S. P., & Schmuck, A. K. (2023). Computing adequately permissive assumptions for synthesis. In TACAS 2023: Tools and Algorithms for the Construction and Analysis of Systems (Vol. 13994, pp. 211–228). Paris, France: Springer Nature. https://doi.org/10.1007/978-3-031-30820-8_15' chicago: 'Anand, Ashwani, Kaushik Mallik, Satya Prakash Nayak, and Anne Kathrin Schmuck. “Computing Adequately Permissive Assumptions for Synthesis.” In TACAS 2023: Tools and Algorithms for the Construction and Analysis of Systems, 13994:211–28. Springer Nature, 2023. https://doi.org/10.1007/978-3-031-30820-8_15.' ieee: 'A. Anand, K. Mallik, S. P. Nayak, and A. K. Schmuck, “Computing adequately permissive assumptions for synthesis,” in TACAS 2023: Tools and Algorithms for the Construction and Analysis of Systems, Paris, France, 2023, vol. 13994, pp. 211–228.' ista: 'Anand A, Mallik K, Nayak SP, Schmuck AK. 2023. Computing adequately permissive assumptions for synthesis. TACAS 2023: Tools and Algorithms for the Construction and Analysis of Systems. TACAS: Tools and Algorithms for the Construction and Analysis of Systems, LNCS, vol. 13994, 211–228.' mla: 'Anand, Ashwani, et al. “Computing Adequately Permissive Assumptions for Synthesis.” TACAS 2023: Tools and Algorithms for the Construction and Analysis of Systems, vol. 13994, Springer Nature, 2023, pp. 211–28, doi:10.1007/978-3-031-30820-8_15.' short: 'A. Anand, K. Mallik, S.P. Nayak, A.K. Schmuck, in:, TACAS 2023: Tools and Algorithms for the Construction and Analysis of Systems, Springer Nature, 2023, pp. 211–228.' conference: end_date: 2023-04-27 location: Paris, France name: 'TACAS: Tools and Algorithms for the Construction and Analysis of Systems' start_date: 2023-04-22 date_created: 2023-06-18T22:00:47Z date_published: 2023-04-20T00:00:00Z date_updated: 2023-06-19T08:49:46Z day: '20' ddc: - '000' department: - _id: ToHe doi: 10.1007/978-3-031-30820-8_15 file: - access_level: open_access checksum: 60dcafc1b4f6f070be43bad3fe877974 content_type: application/pdf creator: dernst date_created: 2023-06-19T08:43:21Z date_updated: 2023-06-19T08:43:21Z file_id: '13151' file_name: 2023_LNCS_Anand.pdf file_size: 521425 relation: main_file success: 1 file_date_updated: 2023-06-19T08:43:21Z has_accepted_license: '1' intvolume: ' 13994' language: - iso: eng month: '04' oa: 1 oa_version: Published Version page: 211-228 publication: 'TACAS 2023: Tools and Algorithms for the Construction and Analysis of Systems' publication_identifier: eissn: - 1611-3349 isbn: - '9783031308192' issn: - 0302-9743 publication_status: published publisher: Springer Nature quality_controlled: '1' scopus_import: '1' status: public title: Computing adequately permissive assumptions for synthesis 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: 13994 year: '2023' ... --- _id: '12826' abstract: - lang: eng text: "During navigation, animals can infer the structure of the environment by computing the optic flow cues elicited by their own movements, and subsequently use this information to instruct proper locomotor actions. These computations require a panoramic assessment of the visual environment in order to disambiguate similar sensory experiences that may require distinct behavioral responses. The estimation of the global motion patterns is therefore essential for successful navigation. Yet, our understanding of the algorithms and implementations that enable coherent panoramic visual perception remains scarce. Here I pursue this problem by dissecting the functional aspects of interneuronal communication in the lobula plate tangential cell network in Drosophila melanogaster. The results presented in the thesis demonstrate that the basis for effective interpretation of the optic flow in this circuit are stereotyped synaptic connections that mediate the formation of distinct subnetworks, each extracting a particular pattern of global motion. \r\nFirstly, I show that gap junctions are essential for a correct interpretation of binocular motion cues by horizontal motion-sensitive cells. HS cells form electrical synapses with contralateral H2 neurons that are involved in detecting yaw rotation and translation. I developed an FlpStop-mediated mutant of a gap junction protein ShakB that disrupts these electrical synapses. While the loss of electrical synapses does not affect the tuning of the direction selectivity in HS neurons, it severely alters their sensitivity to horizontal motion in the contralateral side. These physiological changes result in an inappropriate integration of binocular motion cues in walking animals. While wild-type flies form a binocular perception of visual motion by non-linear integration of monocular optic flow cues, the mutant flies sum the monocular inputs linearly. These results indicate that rather than averaging signals in neighboring neurons, gap-junctions operate in conjunction with chemical synapses to mediate complex non-linear optic flow computations.\r\nSecondly, I show that stochastic manipulation of neuronal activity in the lobula plate tangential cell network is a powerful approach to study the neuronal implementation of optic flow-based navigation in flies. Tangential neurons form multiple subnetworks, each mediating course-stabilizing response to a particular global pattern of visual motion. Application of genetic mosaic techniques can provide sparse optogenetic activation of HS cells in numerous combinations. These distinct combinations of activated neurons drive an array of distinct behavioral responses, providing important insights into how visuomotor transformation is performed in the lobula plate tangential cell network. This approach can be complemented by stochastic silencing of tangential neurons, enabling direct assessment of the functional role of individual tangential neurons in the processing of specific visual motion patterns.\r\n\tTaken together, the findings presented in this thesis suggest that establishing specific activity patterns of tangential cells via stereotyped synaptic connectivity is a key to efficient optic flow-based navigation in Drosophila melanogaster." acknowledged_ssus: - _id: Bio - _id: LifeSc alternative_title: - ISTA Thesis article_processing_charge: No author: - first_name: Victoria full_name: Pokusaeva, Victoria id: 3184041C-F248-11E8-B48F-1D18A9856A87 last_name: Pokusaeva orcid: 0000-0001-7660-444X citation: ama: Pokusaeva V. Neural control of optic flow-based navigation in Drosophila melanogaster. 2023. doi:10.15479/at:ista:12826 apa: Pokusaeva, V. (2023). Neural control of optic flow-based navigation in Drosophila melanogaster. Institute of Science and Technology Austria. https://doi.org/10.15479/at:ista:12826 chicago: Pokusaeva, Victoria. “Neural Control of Optic Flow-Based Navigation in Drosophila Melanogaster.” Institute of Science and Technology Austria, 2023. https://doi.org/10.15479/at:ista:12826. ieee: V. Pokusaeva, “Neural control of optic flow-based navigation in Drosophila melanogaster,” Institute of Science and Technology Austria, 2023. ista: Pokusaeva V. 2023. Neural control of optic flow-based navigation in Drosophila melanogaster. Institute of Science and Technology Austria. mla: Pokusaeva, Victoria. Neural Control of Optic Flow-Based Navigation in Drosophila Melanogaster. Institute of Science and Technology Austria, 2023, doi:10.15479/at:ista:12826. short: V. Pokusaeva, Neural Control of Optic Flow-Based Navigation in Drosophila Melanogaster, Institute of Science and Technology Austria, 2023. date_created: 2023-04-14T14:56:04Z date_published: 2023-04-18T00:00:00Z date_updated: 2023-06-23T09:47:36Z day: '18' ddc: - '570' - '571' degree_awarded: PhD department: - _id: MaJö - _id: GradSch doi: 10.15479/at:ista:12826 ec_funded: 1 file: - access_level: closed checksum: 5f589a9af025f7eeebfd0c186209913e content_type: application/vnd.openxmlformats-officedocument.wordprocessingml.document creator: vpokusae date_created: 2023-04-20T09:14:38Z date_updated: 2023-04-20T09:26:51Z file_id: '12857' file_name: Thesis_Pokusaeva.docx file_size: 14507243 relation: source_file - access_level: open_access checksum: bbeed76db45a996b4c91a9abe12ce0ec content_type: application/pdf creator: vpokusae date_created: 2023-04-20T09:14:44Z date_updated: 2023-04-20T09:14:44Z file_id: '12858' file_name: Thesis_Pokusaeva.pdf file_size: 10090711 relation: main_file success: 1 file_date_updated: 2023-04-20T09:26:51Z has_accepted_license: '1' language: - iso: eng month: '04' oa: 1 oa_version: Published Version page: '106' project: - _id: 2564DBCA-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '665385' name: International IST Doctoral Program publication_identifier: issn: - 2663 - 337X publication_status: published publisher: Institute of Science and Technology Austria status: public supervisor: - first_name: Maximilian A full_name: Jösch, Maximilian A id: 2BD278E6-F248-11E8-B48F-1D18A9856A87 last_name: Jösch orcid: 0000-0002-3937-1330 title: Neural control of optic flow-based navigation in Drosophila melanogaster 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: '2023' ... --- _id: '12086' abstract: - lang: eng text: We present a simple algorithm for computing higher-order Delaunay mosaics that works in Euclidean spaces of any finite dimensions. The algorithm selects the vertices of the order-k mosaic from incrementally constructed lower-order mosaics and uses an algorithm for weighted first-order Delaunay mosaics as a black-box to construct the order-k mosaic from its vertices. Beyond this black-box, the algorithm uses only combinatorial operations, thus facilitating easy implementation. We extend this algorithm to compute higher-order α-shapes and provide open-source implementations. We present experimental results for properties of higher-order Delaunay mosaics of random point sets. acknowledgement: Open access funding provided by Austrian Science Fund (FWF). This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme, Grant No. 788183, from the Wittgenstein Prize, Austrian Science Fund (FWF), Grant No. Z 342-N31, and from the DFG Collaborative Research Center TRR 109, ‘Discretization in Geometry and Dynamics’, Austrian Science Fund (FWF), Grant No. I 02979-N35. article_processing_charge: Yes (via OA deal) article_type: original author: - first_name: Herbert full_name: Edelsbrunner, Herbert id: 3FB178DA-F248-11E8-B48F-1D18A9856A87 last_name: Edelsbrunner orcid: 0000-0002-9823-6833 - first_name: Georg F full_name: Osang, Georg F id: 464B40D6-F248-11E8-B48F-1D18A9856A87 last_name: Osang citation: ama: Edelsbrunner H, Osang GF. A simple algorithm for higher-order Delaunay mosaics and alpha shapes. Algorithmica. 2023;85:277-295. doi:10.1007/s00453-022-01027-6 apa: Edelsbrunner, H., & Osang, G. F. (2023). A simple algorithm for higher-order Delaunay mosaics and alpha shapes. Algorithmica. Springer Nature. https://doi.org/10.1007/s00453-022-01027-6 chicago: Edelsbrunner, Herbert, and Georg F Osang. “A Simple Algorithm for Higher-Order Delaunay Mosaics and Alpha Shapes.” Algorithmica. Springer Nature, 2023. https://doi.org/10.1007/s00453-022-01027-6. ieee: H. Edelsbrunner and G. F. Osang, “A simple algorithm for higher-order Delaunay mosaics and alpha shapes,” Algorithmica, vol. 85. Springer Nature, pp. 277–295, 2023. ista: Edelsbrunner H, Osang GF. 2023. A simple algorithm for higher-order Delaunay mosaics and alpha shapes. Algorithmica. 85, 277–295. mla: Edelsbrunner, Herbert, and Georg F. Osang. “A Simple Algorithm for Higher-Order Delaunay Mosaics and Alpha Shapes.” Algorithmica, vol. 85, Springer Nature, 2023, pp. 277–95, doi:10.1007/s00453-022-01027-6. short: H. Edelsbrunner, G.F. Osang, Algorithmica 85 (2023) 277–295. date_created: 2022-09-11T22:01:57Z date_published: 2023-01-01T00:00:00Z date_updated: 2023-06-27T12:53:43Z day: '01' ddc: - '510' department: - _id: HeEd doi: 10.1007/s00453-022-01027-6 ec_funded: 1 external_id: isi: - '000846967100001' file: - access_level: open_access checksum: 71685ca5121f4c837f40c3f8eb50c915 content_type: application/pdf creator: dernst date_created: 2023-01-20T10:02:48Z date_updated: 2023-01-20T10:02:48Z file_id: '12322' file_name: 2023_Algorithmica_Edelsbrunner.pdf file_size: 911017 relation: main_file success: 1 file_date_updated: 2023-01-20T10:02:48Z has_accepted_license: '1' intvolume: ' 85' isi: 1 language: - iso: eng month: '01' oa: 1 oa_version: Published Version page: 277-295 project: - _id: 266A2E9E-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '788183' name: Alpha Shape Theory Extended - _id: 268116B8-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z00342 name: The Wittgenstein Prize - _id: 2561EBF4-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: I02979-N35 name: Persistence and stability of geometric complexes publication: Algorithmica publication_identifier: eissn: - 1432-0541 issn: - 0178-4617 publication_status: published publisher: Springer Nature quality_controlled: '1' scopus_import: '1' status: public title: A simple algorithm for higher-order Delaunay mosaics and alpha shapes 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: 2EBD1598-F248-11E8-B48F-1D18A9856A87 volume: 85 year: '2023' ... --- _id: '12104' abstract: - lang: eng text: We study ergodic decompositions of Dirichlet spaces under intertwining via unitary order isomorphisms. We show that the ergodic decomposition of a quasi-regular Dirichlet space is unique up to a unique isomorphism of the indexing space. Furthermore, every unitary order isomorphism intertwining two quasi-regular Dirichlet spaces is decomposable over their ergodic decompositions up to conjugation via an isomorphism of the corresponding indexing spaces. acknowledgement: Research supported by the Austrian Science Fund (FWF) grant F65 at the Institute of Science and Technology Austria and by the European Research Council (ERC) (Grant agreement No. 716117 awarded to Prof. Dr. Jan Maas). L.D.S. gratefully acknowledges funding of his current position by the Austrian Science Fund (FWF) through the ESPRIT Programme (Grant No. 208). M.W. gratefully acknowledges funding of his current position by the Austrian Science Fund (FWF) through the ESPRIT Programme (Grant No. 156). article_number: '9' article_processing_charge: Yes (via OA deal) article_type: original author: - first_name: Lorenzo full_name: Dello Schiavo, Lorenzo id: ECEBF480-9E4F-11EA-B557-B0823DDC885E last_name: Dello Schiavo orcid: 0000-0002-9881-6870 - first_name: Melchior full_name: Wirth, Melchior id: 88644358-0A0E-11EA-8FA5-49A33DDC885E last_name: Wirth orcid: 0000-0002-0519-4241 citation: ama: Dello Schiavo L, Wirth M. Ergodic decompositions of Dirichlet forms under order isomorphisms. Journal of Evolution Equations. 2023;23(1). doi:10.1007/s00028-022-00859-7 apa: Dello Schiavo, L., & Wirth, M. (2023). Ergodic decompositions of Dirichlet forms under order isomorphisms. Journal of Evolution Equations. Springer Nature. https://doi.org/10.1007/s00028-022-00859-7 chicago: Dello Schiavo, Lorenzo, and Melchior Wirth. “Ergodic Decompositions of Dirichlet Forms under Order Isomorphisms.” Journal of Evolution Equations. Springer Nature, 2023. https://doi.org/10.1007/s00028-022-00859-7. ieee: L. Dello Schiavo and M. Wirth, “Ergodic decompositions of Dirichlet forms under order isomorphisms,” Journal of Evolution Equations, vol. 23, no. 1. Springer Nature, 2023. ista: Dello Schiavo L, Wirth M. 2023. Ergodic decompositions of Dirichlet forms under order isomorphisms. Journal of Evolution Equations. 23(1), 9. mla: Dello Schiavo, Lorenzo, and Melchior Wirth. “Ergodic Decompositions of Dirichlet Forms under Order Isomorphisms.” Journal of Evolution Equations, vol. 23, no. 1, 9, Springer Nature, 2023, doi:10.1007/s00028-022-00859-7. short: L. Dello Schiavo, M. Wirth, Journal of Evolution Equations 23 (2023). date_created: 2023-01-08T23:00:53Z date_published: 2023-01-01T00:00:00Z date_updated: 2023-06-28T11:54:35Z day: '01' ddc: - '510' department: - _id: JaMa doi: 10.1007/s00028-022-00859-7 ec_funded: 1 external_id: isi: - '000906214600004' file: - access_level: open_access checksum: 1f34f3e2cb521033de6154f274ea3a4e content_type: application/pdf creator: dernst date_created: 2023-01-20T10:45:06Z date_updated: 2023-01-20T10:45:06Z file_id: '12325' file_name: 2023_JourEvolutionEquations_DelloSchiavo.pdf file_size: 422612 relation: main_file success: 1 file_date_updated: 2023-01-20T10:45:06Z has_accepted_license: '1' intvolume: ' 23' isi: 1 issue: '1' language: - iso: eng month: '01' oa: 1 oa_version: Published Version project: - _id: fc31cba2-9c52-11eb-aca3-ff467d239cd2 grant_number: F6504 name: Taming Complexity in Partial Differential Systems - _id: 256E75B8-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '716117' name: Optimal Transport and Stochastic Dynamics - _id: 34dbf174-11ca-11ed-8bc3-afe9d43d4b9c grant_number: E208 name: Configuration Spaces over Non-Smooth Spaces - _id: 34c6ea2d-11ca-11ed-8bc3-c04f3c502833 grant_number: ESP156_N name: Gradient flow techniques for quantum Markov semigroups publication: Journal of Evolution Equations publication_identifier: eissn: - 1424-3202 issn: - 1424-3199 publication_status: published publisher: Springer Nature quality_controlled: '1' scopus_import: '1' status: public title: Ergodic decompositions of Dirichlet forms under order isomorphisms 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: 23 year: '2023' ...