--- _id: '10774' abstract: - lang: eng text: We study the problem of specifying sequential information-flow properties of systems. Information-flow properties are hyperproperties, as they compare different traces of a system. Sequential information-flow properties can express changes, over time, in the information-flow constraints. For example, information-flow constraints during an initialization phase of a system may be different from information-flow constraints that are required during the operation phase. We formalize several variants of interpreting sequential information-flow constraints, which arise from different assumptions about what can be observed of the system. For this purpose, we introduce a first-order logic, called Hypertrace Logic, with both trace and time quantifiers for specifying linear-time hyperproperties. We prove that HyperLTL, which corresponds to a fragment of Hypertrace Logic with restricted quantifier prefixes, cannot specify the majority of the studied variants of sequential information flow, including all variants in which the transition between sequential phases (such as initialization and operation) happens asynchronously. Our results rely on new equivalences between sets of traces that cannot be distinguished by certain classes of formulas from Hypertrace Logic. This presents a new approach to proving inexpressiveness results for HyperLTL. acknowledgement: This work was funded in part by the Wittgenstein Award Z211-N23 of the Austrian Science Fund (FWF) and by the FWF project W1255-N23. alternative_title: - LNCS article_processing_charge: No author: - first_name: Ezio full_name: Bartocci, Ezio last_name: Bartocci - first_name: Thomas full_name: Ferrere, Thomas id: 40960E6E-F248-11E8-B48F-1D18A9856A87 last_name: Ferrere orcid: 0000-0001-5199-3143 - 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: Dejan full_name: Nickovic, Dejan id: 41BCEE5C-F248-11E8-B48F-1D18A9856A87 last_name: Nickovic - first_name: Ana Oliveira full_name: Da Costa, Ana Oliveira last_name: Da Costa citation: ama: 'Bartocci E, Ferrere T, Henzinger TA, Nickovic D, Da Costa AO. Flavors of sequential information flow. In: Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol 13182. Springer Nature; 2022:1-19. doi:10.1007/978-3-030-94583-1_1' apa: 'Bartocci, E., Ferrere, T., Henzinger, T. A., Nickovic, D., & Da Costa, A. O. (2022). Flavors of sequential information flow. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 13182, pp. 1–19). Philadelphia, PA, United States: Springer Nature. https://doi.org/10.1007/978-3-030-94583-1_1' chicago: Bartocci, Ezio, Thomas Ferrere, Thomas A Henzinger, Dejan Nickovic, and Ana Oliveira Da Costa. “Flavors of Sequential Information Flow.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13182:1–19. Springer Nature, 2022. https://doi.org/10.1007/978-3-030-94583-1_1. ieee: E. Bartocci, T. Ferrere, T. A. Henzinger, D. Nickovic, and A. O. Da Costa, “Flavors of sequential information flow,” in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Philadelphia, PA, United States, 2022, vol. 13182, pp. 1–19. ista: 'Bartocci E, Ferrere T, Henzinger TA, Nickovic D, Da Costa AO. 2022. Flavors of sequential information flow. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). VMCAI: Verifcation, Model Checking, and Abstract Interpretation, LNCS, vol. 13182, 1–19.' mla: Bartocci, Ezio, et al. “Flavors of Sequential Information Flow.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13182, Springer Nature, 2022, pp. 1–19, doi:10.1007/978-3-030-94583-1_1. short: E. Bartocci, T. Ferrere, T.A. Henzinger, D. Nickovic, A.O. Da Costa, in:, Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Springer Nature, 2022, pp. 1–19. conference: end_date: 2022-01-18 location: Philadelphia, PA, United States name: 'VMCAI: Verifcation, Model Checking, and Abstract Interpretation' start_date: 2022-01-16 date_created: 2022-02-20T23:01:34Z date_published: 2022-01-14T00:00:00Z date_updated: 2022-08-05T09:02:56Z day: '14' department: - _id: ToHe doi: 10.1007/978-3-030-94583-1_1 external_id: arxiv: - '2105.02013' intvolume: ' 13182' language: - iso: eng main_file_link: - open_access: '1' url: ' https://doi.org/10.48550/arXiv.2105.02013' month: '01' oa: 1 oa_version: Preprint page: 1-19 project: - _id: 25F42A32-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z211 name: The Wittgenstein Prize publication: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) publication_identifier: eissn: - '16113349' isbn: - '9783030945824' issn: - '03029743' publication_status: published publisher: Springer Nature quality_controlled: '1' scopus_import: '1' status: public title: Flavors of sequential information flow type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 13182 year: '2022' ... --- _id: '12010' abstract: - lang: eng text: World models learn behaviors in a latent imagination space to enhance the sample-efficiency of deep reinforcement learning (RL) algorithms. While learning world models for high-dimensional observations (e.g., pixel inputs) has become practicable on standard RL benchmarks and some games, their effectiveness in real-world robotics applications has not been explored. In this paper, we investigate how such agents generalize to real-world autonomous vehicle control tasks, where advanced model-free deep RL algorithms fail. In particular, we set up a series of time-lap tasks for an F1TENTH racing robot, equipped with a high-dimensional LiDAR sensor, on a set of test tracks with a gradual increase in their complexity. In this continuous-control setting, we show that model-based agents capable of learning in imagination substantially outperform model-free agents with respect to performance, sample efficiency, successful task completion, and generalization. Moreover, we show that the generalization ability of model-based agents strongly depends on the choice of their observation model. We provide extensive empirical evidence for the effectiveness of world models provided with long enough memory horizons in sim2real tasks. acknowledgement: L.B. was supported by the Doctoral College Resilient Embedded Systems. M.L. was supported in part by the ERC2020-AdG 101020093 and the Austrian Science Fund (FWF) under grant Z211-N23 (Wittgenstein Award). R.H. and D.R. were supported by The Boeing Company and the Office of Naval Research (ONR) Grant N00014-18-1-2830. R.G. was partially supported by the Horizon-2020 ECSEL Project grant No. 783163 (iDev40) and A.B. by FFG Project ADEX. article_processing_charge: No author: - first_name: Axel full_name: Brunnbauer, Axel last_name: Brunnbauer - first_name: Luigi full_name: Berducci, Luigi last_name: Berducci - first_name: Andreas full_name: Brandstatter, Andreas last_name: Brandstatter - first_name: Mathias full_name: Lechner, Mathias id: 3DC22916-F248-11E8-B48F-1D18A9856A87 last_name: Lechner - first_name: Ramin full_name: Hasani, Ramin last_name: Hasani - first_name: Daniela full_name: Rus, Daniela last_name: Rus - first_name: Radu full_name: Grosu, Radu last_name: Grosu citation: ama: 'Brunnbauer A, Berducci L, Brandstatter A, et al. Latent imagination facilitates zero-shot transfer in autonomous racing. In: 2022 International Conference on Robotics and Automation. IEEE; 2022:7513-7520. doi:10.1109/ICRA46639.2022.9811650' apa: 'Brunnbauer, A., Berducci, L., Brandstatter, A., Lechner, M., Hasani, R., Rus, D., & Grosu, R. (2022). Latent imagination facilitates zero-shot transfer in autonomous racing. In 2022 International Conference on Robotics and Automation (pp. 7513–7520). Philadelphia, PA, United States: IEEE. https://doi.org/10.1109/ICRA46639.2022.9811650' chicago: Brunnbauer, Axel, Luigi Berducci, Andreas Brandstatter, Mathias Lechner, Ramin Hasani, Daniela Rus, and Radu Grosu. “Latent Imagination Facilitates Zero-Shot Transfer in Autonomous Racing.” In 2022 International Conference on Robotics and Automation, 7513–20. IEEE, 2022. https://doi.org/10.1109/ICRA46639.2022.9811650. ieee: A. Brunnbauer et al., “Latent imagination facilitates zero-shot transfer in autonomous racing,” in 2022 International Conference on Robotics and Automation, Philadelphia, PA, United States, 2022, pp. 7513–7520. ista: 'Brunnbauer A, Berducci L, Brandstatter A, Lechner M, Hasani R, Rus D, Grosu R. 2022. Latent imagination facilitates zero-shot transfer in autonomous racing. 2022 International Conference on Robotics and Automation. ICRA: International Conference on Robotics and Automation, 7513–7520.' mla: Brunnbauer, Axel, et al. “Latent Imagination Facilitates Zero-Shot Transfer in Autonomous Racing.” 2022 International Conference on Robotics and Automation, IEEE, 2022, pp. 7513–20, doi:10.1109/ICRA46639.2022.9811650. short: A. Brunnbauer, L. Berducci, A. Brandstatter, M. Lechner, R. Hasani, D. Rus, R. Grosu, in:, 2022 International Conference on Robotics and Automation, IEEE, 2022, pp. 7513–7520. conference: end_date: 2022-05-27 location: Philadelphia, PA, United States name: 'ICRA: International Conference on Robotics and Automation' start_date: 2022-05-23 date_created: 2022-09-04T22:02:02Z date_published: 2022-07-12T00:00:00Z date_updated: 2022-09-05T08:46:12Z day: '12' department: - _id: ToHe doi: 10.1109/ICRA46639.2022.9811650 ec_funded: 1 external_id: arxiv: - '2103.04909' language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.48550/arXiv.2103.04909 month: '07' oa: 1 oa_version: Preprint page: 7513-7520 project: - _id: 62781420-2b32-11ec-9570-8d9b63373d4d call_identifier: H2020 grant_number: '101020093' name: Vigilant Algorithmic Monitoring of Software - _id: 25F42A32-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z211 name: The Wittgenstein Prize publication: 2022 International Conference on Robotics and Automation publication_identifier: isbn: - '9781728196817' issn: - 1050-4729 publication_status: published publisher: IEEE quality_controlled: '1' scopus_import: '1' status: public title: Latent imagination facilitates zero-shot transfer in autonomous racing type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2022' ... --- _id: '12171' abstract: - lang: eng text: 'We propose an algorithmic approach for synthesizing linear hybrid automata from time-series data. Unlike existing approaches, our approach provides a whole family of models with the same discrete structure but different dynamics. Each model in the family is guaranteed to capture the input data up to a precision error ε, in the following sense: For each time series, the model contains an execution that is ε-close to the data points. Our construction allows to effectively choose a model from this family with minimal precision error ε. We demonstrate the algorithm’s efficiency and its ability to find precise models in two case studies.' acknowledgement: This work was supported in part by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement no. 847635, by the ERC-2020-AdG 101020093, by DIREC - Digital Research Centre Denmark, and by the Villum Investigator Grant S4OS. alternative_title: - LNCS article_processing_charge: No author: - first_name: Miriam full_name: Garcia Soto, Miriam id: 4B3207F6-F248-11E8-B48F-1D18A9856A87 last_name: Garcia Soto orcid: 0000-0003-2936-5719 - 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: Christian full_name: Schilling, Christian id: 3A2F4DCE-F248-11E8-B48F-1D18A9856A87 last_name: Schilling orcid: 0000-0003-3658-1065 citation: ama: 'Garcia Soto M, Henzinger TA, Schilling C. Synthesis of parametric hybrid automata from time series. In: 20th International Symposium on Automated Technology for Verification and Analysis. Vol 13505. Springer Nature; 2022:337-353. doi:10.1007/978-3-031-19992-9_22' apa: 'Garcia Soto, M., Henzinger, T. A., & Schilling, C. (2022). Synthesis of parametric hybrid automata from time series. In 20th International Symposium on Automated Technology for Verification and Analysis (Vol. 13505, pp. 337–353). Virtual: Springer Nature. https://doi.org/10.1007/978-3-031-19992-9_22' chicago: Garcia Soto, Miriam, Thomas A Henzinger, and Christian Schilling. “Synthesis of Parametric Hybrid Automata from Time Series.” In 20th International Symposium on Automated Technology for Verification and Analysis, 13505:337–53. Springer Nature, 2022. https://doi.org/10.1007/978-3-031-19992-9_22. ieee: M. Garcia Soto, T. A. Henzinger, and C. Schilling, “Synthesis of parametric hybrid automata from time series,” in 20th International Symposium on Automated Technology for Verification and Analysis, Virtual, 2022, vol. 13505, pp. 337–353. ista: 'Garcia Soto M, Henzinger TA, Schilling C. 2022. Synthesis of parametric hybrid automata from time series. 20th International Symposium on Automated Technology for Verification and Analysis. ATVA: Automated Technology for Verification and Analysis, LNCS, vol. 13505, 337–353.' mla: Garcia Soto, Miriam, et al. “Synthesis of Parametric Hybrid Automata from Time Series.” 20th International Symposium on Automated Technology for Verification and Analysis, vol. 13505, Springer Nature, 2022, pp. 337–53, doi:10.1007/978-3-031-19992-9_22. short: M. Garcia Soto, T.A. Henzinger, C. Schilling, in:, 20th International Symposium on Automated Technology for Verification and Analysis, Springer Nature, 2022, pp. 337–353. conference: end_date: 2022-10-28 location: Virtual name: 'ATVA: Automated Technology for Verification and Analysis' start_date: 2022-10-25 date_created: 2023-01-12T12:11:16Z date_published: 2022-10-21T00:00:00Z date_updated: 2023-02-13T09:27:55Z day: '21' department: - _id: ToHe doi: 10.1007/978-3-031-19992-9_22 ec_funded: 1 external_id: arxiv: - '2208.06383' intvolume: ' 13505' language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.48550/arXiv.2208.06383 month: '10' oa: 1 oa_version: Preprint page: 337-353 project: - _id: 62781420-2b32-11ec-9570-8d9b63373d4d call_identifier: H2020 grant_number: '101020093' name: Vigilant Algorithmic Monitoring of Software publication: 20th International Symposium on Automated Technology for Verification and Analysis publication_identifier: eisbn: - '9783031199929' eissn: - 1611-3349 isbn: - '9783031199912' issn: - 0302-9743 publication_status: published publisher: Springer Nature quality_controlled: '1' scopus_import: '1' status: public title: Synthesis of parametric hybrid automata from time series type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 13505 year: '2022' ... --- _id: '12508' abstract: - lang: eng text: "We explore the notion of history-determinism in the context of timed automata (TA). History-deterministic automata are those in which nondeterminism can be resolved on the fly, based on the run constructed thus far. History-determinism is a robust property that admits different game-based characterisations, and history-deterministic specifications allow for game-based verification without an expensive determinization step.\r\nWe show yet another characterisation of history-determinism in terms of fair simulation, at the general level of labelled transition systems: a system is history-deterministic precisely if and only if it fairly simulates all language smaller systems.\r\nFor timed automata over infinite timed words it is known that universality is undecidable for Büchi TA. We show that for history-deterministic TA with arbitrary parity acceptance, timed universality, inclusion, and synthesis all remain decidable and are ExpTime-complete.\r\nFor the subclass of TA with safety or reachability acceptance, we show that checking whether such an automaton is history-deterministic is decidable (in ExpTime), and history-deterministic TA with safety acceptance are effectively determinizable without introducing new automata states." acknowledgement: "Thomas A. Henzinger: This work was supported in part by the ERC-2020-AdG 101020093.\r\nPatrick Totzke: acknowledges support from the EPSRC, project no. EP/V025848/1.\r\n" alternative_title: - LIPIcs article_processing_charge: No author: - 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: Karoliina full_name: Lehtinen, Karoliina last_name: Lehtinen - first_name: Patrick full_name: Totzke, Patrick last_name: Totzke citation: ama: 'Henzinger TA, Lehtinen K, Totzke P. History-deterministic timed automata. In: 33rd International Conference on Concurrency Theory. Vol 243. Schloss Dagstuhl - Leibniz-Zentrum für Informatik; 2022:14:1-14:21. doi:10.4230/LIPIcs.CONCUR.2022.14' apa: 'Henzinger, T. A., Lehtinen, K., & Totzke, P. (2022). History-deterministic timed automata. In 33rd International Conference on Concurrency Theory (Vol. 243, p. 14:1-14:21). Warsaw, Poland: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.CONCUR.2022.14' chicago: Henzinger, Thomas A, Karoliina Lehtinen, and Patrick Totzke. “History-Deterministic Timed Automata.” In 33rd International Conference on Concurrency Theory, 243:14:1-14:21. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022. https://doi.org/10.4230/LIPIcs.CONCUR.2022.14. ieee: T. A. Henzinger, K. Lehtinen, and P. Totzke, “History-deterministic timed automata,” in 33rd International Conference on Concurrency Theory, Warsaw, Poland, 2022, vol. 243, p. 14:1-14:21. ista: 'Henzinger TA, Lehtinen K, Totzke P. 2022. History-deterministic timed automata. 33rd International Conference on Concurrency Theory. CONCUR: Conference on Concurrency Theory, LIPIcs, vol. 243, 14:1-14:21.' mla: Henzinger, Thomas A., et al. “History-Deterministic Timed Automata.” 33rd International Conference on Concurrency Theory, vol. 243, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022, p. 14:1-14:21, doi:10.4230/LIPIcs.CONCUR.2022.14. short: T.A. Henzinger, K. Lehtinen, P. Totzke, in:, 33rd International Conference on Concurrency Theory, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022, p. 14:1-14:21. conference: end_date: 2022-09-16 location: Warsaw, Poland name: 'CONCUR: Conference on Concurrency Theory' start_date: 2022-09-13 date_created: 2023-02-05T17:24:23Z date_published: 2022-09-06T00:00:00Z date_updated: 2023-02-06T09:23:31Z day: '06' ddc: - '000' department: - _id: ToHe doi: 10.4230/LIPIcs.CONCUR.2022.14 ec_funded: 1 file: - access_level: open_access checksum: 9e97e15628f66b2ad77f535bb0327dee content_type: application/pdf creator: dernst date_created: 2023-02-06T09:21:09Z date_updated: 2023-02-06T09:21:09Z file_id: '12520' file_name: 2022_LIPICs_Henzinger2.pdf file_size: 717940 relation: main_file success: 1 file_date_updated: 2023-02-06T09:21:09Z has_accepted_license: '1' intvolume: ' 243' language: - iso: eng license: https://creativecommons.org/licenses/by/4.0/ month: '09' oa: 1 oa_version: Published Version page: 14:1-14:21 project: - _id: 62781420-2b32-11ec-9570-8d9b63373d4d call_identifier: H2020 grant_number: '101020093' name: Vigilant Algorithmic Monitoring of Software publication: 33rd International Conference on Concurrency Theory publication_identifier: isbn: - '9783959772464' issn: - 1868-8969 publication_status: published publisher: Schloss Dagstuhl - Leibniz-Zentrum für Informatik quality_controlled: '1' scopus_import: '1' status: public title: History-deterministic timed 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: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 243 year: '2022' ... --- _id: '12509' abstract: - lang: eng text: A graph game is a two-player zero-sum game in which the players move a token throughout a graph to produce an infinite path, which determines the winner or payoff of the game. In bidding games, both players have budgets, and in each turn, we hold an "auction" (bidding) to determine which player moves the token. In this survey, we consider several bidding mechanisms and their effect on the properties of the game. Specifically, bidding games, and in particular bidding games of infinite duration, have an intriguing equivalence with random-turn games in which in each turn, the player who moves is chosen randomly. We summarize how minor changes in the bidding mechanism lead to unexpected differences in the equivalence with random-turn games. acknowledgement: "Guy Avni: Work partially supported by the Israel Science Foundation, ISF grant agreement\r\nno 1679/21.\r\nThomas A. Henzinger: This work was supported in part by the ERC-2020-AdG 101020093.\r\nWe would like to thank all our collaborators Milad Aghajohari, Ventsislav Chonev, Rasmus Ibsen-Jensen, Ismäel Jecker, Petr Novotný, Josef Tkadlec, and Ðorđe Žikelić; we hope the collaboration was as fun and meaningful for you as it was for us." article_processing_charge: No author: - first_name: Guy full_name: Avni, Guy id: 463C8BC2-F248-11E8-B48F-1D18A9856A87 last_name: Avni orcid: 0000-0001-5588-8287 - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000-0002-2985-7724 citation: ama: 'Avni G, Henzinger TA. An updated survey of bidding games on graphs. In: 47th International Symposium on Mathematical Foundations of Computer Science. Vol 241. Leibniz International Proceedings in Informatics (LIPIcs). Dagstuhl, Germany: Schloss Dagstuhl - Leibniz-Zentrum für Informatik; 2022:3:1-3:6. doi:10.4230/LIPIcs.MFCS.2022.3' apa: 'Avni, G., & Henzinger, T. A. (2022). An updated survey of bidding games on graphs. In 47th International Symposium on Mathematical Foundations of Computer Science (Vol. 241, p. 3:1-3:6). Dagstuhl, Germany: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.MFCS.2022.3' chicago: 'Avni, Guy, and Thomas A Henzinger. “An Updated Survey of Bidding Games on Graphs.” In 47th International Symposium on Mathematical Foundations of Computer Science, 241:3:1-3:6. Leibniz International Proceedings in Informatics (LIPIcs). Dagstuhl, Germany: Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022. https://doi.org/10.4230/LIPIcs.MFCS.2022.3.' ieee: G. Avni and T. A. Henzinger, “An updated survey of bidding games on graphs,” in 47th International Symposium on Mathematical Foundations of Computer Science, Vienna, Austria, 2022, vol. 241, p. 3:1-3:6. ista: 'Avni G, Henzinger TA. 2022. An updated survey of bidding games on graphs. 47th International Symposium on Mathematical Foundations of Computer Science. MFCS: Symposium on Mathematical Foundations of Computer ScienceLeibniz International Proceedings in Informatics (LIPIcs) vol. 241, 3:1-3:6.' mla: Avni, Guy, and Thomas A. Henzinger. “An Updated Survey of Bidding Games on Graphs.” 47th International Symposium on Mathematical Foundations of Computer Science, vol. 241, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022, p. 3:1-3:6, doi:10.4230/LIPIcs.MFCS.2022.3. short: G. Avni, T.A. Henzinger, in:, 47th International Symposium on Mathematical Foundations of Computer Science, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, Dagstuhl, Germany, 2022, p. 3:1-3:6. conference: end_date: 2022-08-26 location: Vienna, Austria name: 'MFCS: Symposium on Mathematical Foundations of Computer Science' start_date: 2022-08-22 date_created: 2023-02-05T17:26:01Z date_published: 2022-08-22T00:00:00Z date_updated: 2023-02-06T09:16:54Z day: '22' ddc: - '000' department: - _id: ToHe doi: 10.4230/LIPIcs.MFCS.2022.3 ec_funded: 1 file: - access_level: open_access checksum: 1888ec9421622f9526fbec2de035f132 content_type: application/pdf creator: dernst date_created: 2023-02-06T09:13:04Z date_updated: 2023-02-06T09:13:04Z file_id: '12519' file_name: 2022_LIPICs_Avni.pdf file_size: 624586 relation: main_file success: 1 file_date_updated: 2023-02-06T09:13:04Z has_accepted_license: '1' intvolume: ' 241' language: - iso: eng month: '08' oa: 1 oa_version: Published Version page: 3:1-3:6 place: Dagstuhl, Germany project: - _id: 62781420-2b32-11ec-9570-8d9b63373d4d call_identifier: H2020 grant_number: '101020093' name: Vigilant Algorithmic Monitoring of Software publication: 47th International Symposium on Mathematical Foundations of Computer Science publication_identifier: isbn: - '9783959772563' issn: - 1868-8969 publication_status: published publisher: Schloss Dagstuhl - Leibniz-Zentrum für Informatik quality_controlled: '1' scopus_import: '1' series_title: Leibniz International Proceedings in Informatics (LIPIcs) status: public title: An updated survey of bidding games on graphs 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: 241 year: '2022' ... --- _id: '11366' abstract: - lang: eng text: "Adversarial training (i.e., training on adversarially perturbed input data) is a well-studied method for making neural networks robust to potential adversarial attacks during inference. However, the improved robustness does not\r\ncome for free but rather is accompanied by a decrease in overall model accuracy and performance. Recent work has shown that, in practical robot learning applications, the effects of adversarial training do not pose a fair trade-off\r\nbut inflict a net loss when measured in holistic robot performance. This work revisits the robustness-accuracy trade-off in robot learning by systematically analyzing if recent advances in robust training methods and theory in\r\nconjunction with adversarial robot learning can make adversarial training suitable for real-world robot applications. We evaluate a wide variety of robot learning tasks ranging from autonomous driving in a high-fidelity environment\r\namenable to sim-to-real deployment, to mobile robot gesture recognition. Our results demonstrate that, while these techniques make incremental improvements on the trade-off on a relative scale, the negative side-effects caused by\r\nadversarial training still outweigh the improvements by an order of magnitude. We conclude that more substantial advances in robust learning methods are necessary before they can benefit robot learning tasks in practice." acknowledgement: "This work was supported in parts by the ERC-2020-AdG 101020093, National Science Foundation (NSF), and JP\r\nMorgan Graduate Fellowships. We thank Christoph Lampert for inspiring this work.\r\n" article_number: '2204.07373' article_processing_charge: No author: - first_name: Mathias full_name: Lechner, Mathias id: 3DC22916-F248-11E8-B48F-1D18A9856A87 last_name: Lechner - first_name: Alexander full_name: Amini, Alexander last_name: Amini - first_name: Daniela full_name: Rus, Daniela last_name: Rus - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000-0002-2985-7724 citation: ama: Lechner M, Amini A, Rus D, Henzinger TA. Revisiting the adversarial robustness-accuracy tradeoff in robot learning. arXiv. doi:10.48550/arXiv.2204.07373 apa: Lechner, M., Amini, A., Rus, D., & Henzinger, T. A. (n.d.). Revisiting the adversarial robustness-accuracy tradeoff in robot learning. arXiv. https://doi.org/10.48550/arXiv.2204.07373 chicago: Lechner, Mathias, Alexander Amini, Daniela Rus, and Thomas A Henzinger. “Revisiting the Adversarial Robustness-Accuracy Tradeoff in Robot Learning.” ArXiv, n.d. https://doi.org/10.48550/arXiv.2204.07373. ieee: M. Lechner, A. Amini, D. Rus, and T. A. Henzinger, “Revisiting the adversarial robustness-accuracy tradeoff in robot learning,” arXiv. . ista: Lechner M, Amini A, Rus D, Henzinger TA. Revisiting the adversarial robustness-accuracy tradeoff in robot learning. arXiv, 2204.07373. mla: Lechner, Mathias, et al. “Revisiting the Adversarial Robustness-Accuracy Tradeoff in Robot Learning.” ArXiv, 2204.07373, doi:10.48550/arXiv.2204.07373. short: M. Lechner, A. Amini, D. Rus, T.A. Henzinger, ArXiv (n.d.). date_created: 2022-05-12T13:20:17Z date_published: 2022-04-15T00:00:00Z date_updated: 2023-08-01T13:36:50Z day: '15' department: - _id: ToHe doi: 10.48550/arXiv.2204.07373 ec_funded: 1 external_id: arxiv: - '2204.07373' language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.48550/arXiv.2204.07373 month: '04' oa: 1 oa_version: Preprint project: - _id: 62781420-2b32-11ec-9570-8d9b63373d4d call_identifier: H2020 grant_number: '101020093' name: Vigilant Algorithmic Monitoring of Software publication: arXiv publication_status: submitted related_material: record: - id: '11362' relation: dissertation_contains status: public - id: '12704' relation: later_version status: public status: public title: Revisiting the adversarial robustness-accuracy tradeoff in robot learning type: preprint user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2022' ... --- _id: '10891' abstract: - lang: eng text: We present a formal framework for the online black-box monitoring of software using monitors with quantitative verdict functions. Quantitative verdict functions have several advantages. First, quantitative monitors can be approximate, i.e., the value of the verdict function does not need to correspond exactly to the value of the property under observation. Second, quantitative monitors can be quantified universally, i.e., for every possible observed behavior, the monitor tries to make the best effort to estimate the value of the property under observation. Third, quantitative monitors can watch boolean as well as quantitative properties, such as average response time. Fourth, quantitative monitors can use non-finite-state resources, such as counters. As a consequence, quantitative monitors can be compared according to how many resources they use (e.g., the number of counters) and how precisely they approximate the property under observation. This allows for a rich spectrum of cost-precision trade-offs in monitoring software. acknowledgement: The formal framework for quantitative monitoring which is presented in this invited talk was defined jointly with N. Ege Saraç at LICS 2021. This work was supported in part by the Wittgenstein Award Z211-N23 of the Austrian Science Fund. article_processing_charge: No author: - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000-0002-2985-7724 citation: ama: 'Henzinger TA. Quantitative monitoring of software. In: Software Verification. Vol 13124. LNCS. Springer Nature; 2022:3-6. doi:10.1007/978-3-030-95561-8_1' apa: 'Henzinger, T. A. (2022). Quantitative monitoring of software. In Software Verification (Vol. 13124, pp. 3–6). New Haven, CT, United States: Springer Nature. https://doi.org/10.1007/978-3-030-95561-8_1' chicago: Henzinger, Thomas A. “Quantitative Monitoring of Software.” In Software Verification, 13124:3–6. LNCS. Springer Nature, 2022. https://doi.org/10.1007/978-3-030-95561-8_1. ieee: T. A. Henzinger, “Quantitative monitoring of software,” in Software Verification, New Haven, CT, United States, 2022, vol. 13124, pp. 3–6. ista: 'Henzinger TA. 2022. Quantitative monitoring of software. Software Verification. NSV: Numerical Software VerificationLNCS vol. 13124, 3–6.' mla: Henzinger, Thomas A. “Quantitative Monitoring of Software.” Software Verification, vol. 13124, Springer Nature, 2022, pp. 3–6, doi:10.1007/978-3-030-95561-8_1. short: T.A. Henzinger, in:, Software Verification, Springer Nature, 2022, pp. 3–6. conference: end_date: 2021-10-19 location: New Haven, CT, United States name: 'NSV: Numerical Software Verification' start_date: 2021-10-18 date_created: 2022-03-20T23:01:40Z date_published: 2022-02-22T00:00:00Z date_updated: 2023-08-03T06:11:55Z day: '22' department: - _id: ToHe doi: 10.1007/978-3-030-95561-8_1 external_id: isi: - '000771713200001' intvolume: ' 13124' isi: 1 language: - iso: eng month: '02' oa_version: None page: 3-6 project: - _id: 25F42A32-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z211 name: The Wittgenstein Prize publication: Software Verification publication_identifier: eissn: - 1611-3349 isbn: - '9783030955601' issn: - 0302-9743 publication_status: published publisher: Springer Nature quality_controlled: '1' scopus_import: '1' series_title: LNCS status: public title: Quantitative monitoring of software type: conference user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 13124 year: '2022' ... --- _id: '11355' abstract: - lang: eng text: "Contract-based design is a promising methodology for taming the complexity of developing sophisticated systems. A formal contract distinguishes between assumptions, which are constraints that the designer of a component puts on the environments in which the component can be used safely, and guarantees, which are promises that the designer asks from the team that implements the component. A theory of formal contracts can be formalized as an interface theory, which supports the composition and refinement of both assumptions and guarantees.\r\nAlthough there is a rich landscape of contract-based design methods that address functional and extra-functional properties, we present the first interface theory that is designed for ensuring system-wide security properties. Our framework provides a refinement relation and a composition operation that support both incremental design and independent implementability. We develop our theory for both stateless and stateful interfaces. We illustrate the applicability of our framework with an example inspired from the automotive domain." acknowledgement: This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 956123 and was funded in part by the FWF project W1255-N23 and by the ERC-2020-AdG 101020093. alternative_title: - LNCS article_processing_charge: No author: - first_name: Ezio full_name: Bartocci, Ezio last_name: Bartocci - first_name: Thomas full_name: Ferrere, Thomas id: 40960E6E-F248-11E8-B48F-1D18A9856A87 last_name: Ferrere orcid: 0000-0001-5199-3143 - 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: Dejan full_name: Nickovic, Dejan id: 41BCEE5C-F248-11E8-B48F-1D18A9856A87 last_name: Nickovic - first_name: Ana Oliveira full_name: Da Costa, Ana Oliveira last_name: Da Costa citation: ama: 'Bartocci E, Ferrere T, Henzinger TA, Nickovic D, Da Costa AO. Information-flow interfaces. In: Fundamental Approaches to Software Engineering. Vol 13241. Springer Nature; 2022:3-22. doi:10.1007/978-3-030-99429-7_1' apa: 'Bartocci, E., Ferrere, T., Henzinger, T. A., Nickovic, D., & Da Costa, A. O. (2022). Information-flow interfaces. In Fundamental Approaches to Software Engineering (Vol. 13241, pp. 3–22). Munich, Germany: Springer Nature. https://doi.org/10.1007/978-3-030-99429-7_1' chicago: Bartocci, Ezio, Thomas Ferrere, Thomas A Henzinger, Dejan Nickovic, and Ana Oliveira Da Costa. “Information-Flow Interfaces.” In Fundamental Approaches to Software Engineering, 13241:3–22. Springer Nature, 2022. https://doi.org/10.1007/978-3-030-99429-7_1. ieee: E. Bartocci, T. Ferrere, T. A. Henzinger, D. Nickovic, and A. O. Da Costa, “Information-flow interfaces,” in Fundamental Approaches to Software Engineering, Munich, Germany, 2022, vol. 13241, pp. 3–22. ista: 'Bartocci E, Ferrere T, Henzinger TA, Nickovic D, Da Costa AO. 2022. Information-flow interfaces. Fundamental Approaches to Software Engineering. FASE: Fundamental Approaches to Software Engineering, LNCS, vol. 13241, 3–22.' mla: Bartocci, Ezio, et al. “Information-Flow Interfaces.” Fundamental Approaches to Software Engineering, vol. 13241, Springer Nature, 2022, pp. 3–22, doi:10.1007/978-3-030-99429-7_1. short: E. Bartocci, T. Ferrere, T.A. Henzinger, D. Nickovic, A.O. Da Costa, in:, Fundamental Approaches to Software Engineering, Springer Nature, 2022, pp. 3–22. conference: end_date: 2022-04-07 location: Munich, Germany name: 'FASE: Fundamental Approaches to Software Engineering' start_date: 2022-04-02 date_created: 2022-05-08T22:01:44Z date_published: 2022-03-29T00:00:00Z date_updated: 2023-08-03T07:03:40Z day: '29' ddc: - '000' department: - _id: ToHe doi: 10.1007/978-3-030-99429-7_1 ec_funded: 1 external_id: isi: - '000782393600001' file: - access_level: open_access checksum: 7f6f860b20b8de2a249e9c1b4eee15cf content_type: application/pdf creator: dernst date_created: 2022-05-09T06:52:44Z date_updated: 2022-05-09T06:52:44Z file_id: '11357' file_name: 2022_LNCS_Bartocci.pdf file_size: 479146 relation: main_file success: 1 file_date_updated: 2022-05-09T06:52:44Z has_accepted_license: '1' intvolume: ' 13241' isi: 1 language: - iso: eng month: '03' oa: 1 oa_version: Published Version page: 3-22 project: - _id: 62781420-2b32-11ec-9570-8d9b63373d4d call_identifier: H2020 grant_number: '101020093' name: Vigilant Algorithmic Monitoring of Software publication: Fundamental Approaches to Software Engineering publication_identifier: eissn: - 1611-3349 isbn: - '9783030994280' issn: - 0302-9743 publication_status: published publisher: Springer Nature quality_controlled: '1' scopus_import: '1' status: public title: Information-flow interfaces 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: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 13241 year: '2022' ... --- _id: '11775' abstract: - lang: eng text: 'Quantitative monitoring can be universal and approximate: For every finite sequence of observations, the specification provides a value and the monitor outputs a best-effort approximation of it. The quality of the approximation may depend on the resources that are available to the monitor. By taking to the limit the sequences of specification values and monitor outputs, we obtain precision-resource trade-offs also for limit monitoring. This paper provides a formal framework for studying such trade-offs using an abstract interpretation for monitors: For each natural number n, the aggregate semantics of a monitor at time n is an equivalence relation over all sequences of at most n observations so that two equivalent sequences are indistinguishable to the monitor and thus mapped to the same output. This abstract interpretation of quantitative monitors allows us to measure the number of equivalence classes (or “resource use”) that is necessary for a certain precision up to a certain time, or at any time. Our framework offers several insights. For example, we identify a family of specifications for which any resource-optimal exact limit monitor is independent of any error permitted over finite traces. Moreover, we present a specification for which any resource-optimal approximate limit monitor does not minimize its resource use at any time. ' acknowledgement: We thank the anonymous reviewers for their helpful comments. This work was supported in part by the ERC-2020-AdG 101020093. alternative_title: - LNCS article_processing_charge: Yes author: - 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: 'Henzinger TA, Mazzocchi NA, Sarac NE. Abstract monitors for quantitative specifications. In: 22nd International Conference on Runtime Verification. Vol 13498. Springer Nature; 2022:200-220. doi:10.1007/978-3-031-17196-3_11' apa: 'Henzinger, T. A., Mazzocchi, N. A., & Sarac, N. E. (2022). Abstract monitors for quantitative specifications. In 22nd International Conference on Runtime Verification (Vol. 13498, pp. 200–220). Tbilisi, Georgia: Springer Nature. https://doi.org/10.1007/978-3-031-17196-3_11' chicago: Henzinger, Thomas A, Nicolas Adrien Mazzocchi, and Naci E Sarac. “Abstract Monitors for Quantitative Specifications.” In 22nd International Conference on Runtime Verification, 13498:200–220. Springer Nature, 2022. https://doi.org/10.1007/978-3-031-17196-3_11. ieee: T. A. Henzinger, N. A. Mazzocchi, and N. E. Sarac, “Abstract monitors for quantitative specifications,” in 22nd International Conference on Runtime Verification, Tbilisi, Georgia, 2022, vol. 13498, pp. 200–220. ista: 'Henzinger TA, Mazzocchi NA, Sarac NE. 2022. Abstract monitors for quantitative specifications. 22nd International Conference on Runtime Verification. RV: Runtime Verification, LNCS, vol. 13498, 200–220.' mla: Henzinger, Thomas A., et al. “Abstract Monitors for Quantitative Specifications.” 22nd International Conference on Runtime Verification, vol. 13498, Springer Nature, 2022, pp. 200–20, doi:10.1007/978-3-031-17196-3_11. short: T.A. Henzinger, N.A. Mazzocchi, N.E. Sarac, in:, 22nd International Conference on Runtime Verification, Springer Nature, 2022, pp. 200–220. conference: end_date: 2022-09-30 location: Tbilisi, Georgia name: 'RV: Runtime Verification' start_date: 2022-09-28 date_created: 2022-08-08T17:09:09Z date_published: 2022-09-23T00:00:00Z date_updated: 2023-08-03T13:38:46Z day: '23' ddc: - '000' department: - _id: GradSch - _id: ToHe doi: 10.1007/978-3-031-17196-3_11 ec_funded: 1 external_id: isi: - '000866539700011' file: - access_level: open_access checksum: 05c7dcfbb9053a98f46441fb2eccb213 content_type: application/pdf creator: dernst date_created: 2023-01-20T07:34:50Z date_updated: 2023-01-20T07:34:50Z file_id: '12317' file_name: 2022_LNCS_RV_Henzinger.pdf file_size: 477110 relation: main_file success: 1 file_date_updated: 2023-01-20T07:34:50Z has_accepted_license: '1' intvolume: ' 13498' isi: 1 language: - iso: eng month: '09' oa: 1 oa_version: Published Version page: 200-220 project: - _id: 62781420-2b32-11ec-9570-8d9b63373d4d call_identifier: H2020 grant_number: '101020093' name: Vigilant Algorithmic Monitoring of Software publication: 22nd International Conference on Runtime Verification publication_identifier: issn: - 0302-9743 publication_status: published publisher: Springer Nature quality_controlled: '1' scopus_import: '1' status: public title: Abstract monitors for quantitative specifications 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: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 13498 year: '2022' ... --- _id: '12147' abstract: - lang: eng text: Continuous-time neural networks are a class of machine learning systems that can tackle representation learning on spatiotemporal decision-making tasks. These models are typically represented by continuous differential equations. However, their expressive power when they are deployed on computers is bottlenecked by numerical differential equation solvers. This limitation has notably slowed down the scaling and understanding of numerous natural physical phenomena such as the dynamics of nervous systems. Ideally, we would circumvent this bottleneck by solving the given dynamical system in closed form. This is known to be intractable in general. Here, we show that it is possible to closely approximate the interaction between neurons and synapses—the building blocks of natural and artificial neural networks—constructed by liquid time-constant networks efficiently in closed form. To this end, we compute a tightly bounded approximation of the solution of an integral appearing in liquid time-constant dynamics that has had no known closed-form solution so far. This closed-form solution impacts the design of continuous-time and continuous-depth neural models. For instance, since time appears explicitly in closed form, the formulation relaxes the need for complex numerical solvers. Consequently, we obtain models that are between one and five orders of magnitude faster in training and inference compared with differential equation-based counterparts. More importantly, in contrast to ordinary differential equation-based continuous networks, closed-form networks can scale remarkably well compared with other deep learning instances. Lastly, as these models are derived from liquid networks, they show good performance in time-series modelling compared with advanced recurrent neural network models. acknowledgement: This research was supported in part by the AI2050 program at Schmidt Futures (grant G-22-63172), the Boeing Company, and the United States Air Force Research Laboratory and the United States Air Force Artificial Intelligence Accelerator and was accomplished under cooperative agreement number FA8750-19-2-1000. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the United States Air Force or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes, notwithstanding any copyright notation herein. This work was further supported by The Boeing Company and Office of Naval Research grant N00014-18-1-2830. M.T. is supported by the Poul Due Jensen Foundation, grant 883901. M.L. was supported in part by the Austrian Science Fund under grant Z211-N23 (Wittgenstein Award). A.A. was supported by the National Science Foundation Graduate Research Fellowship Program. We thank T.-H. Wang, P. Kao, M. Chahine, W. Xiao, X. Li, L. Yin and Y. Ben for useful suggestions and for testing of CfC models to confirm the results across other domains. article_processing_charge: No article_type: original author: - first_name: Ramin full_name: Hasani, Ramin last_name: Hasani - first_name: Mathias full_name: Lechner, Mathias id: 3DC22916-F248-11E8-B48F-1D18A9856A87 last_name: Lechner - first_name: Alexander full_name: Amini, Alexander last_name: Amini - first_name: Lucas full_name: Liebenwein, Lucas last_name: Liebenwein - first_name: Aaron full_name: Ray, Aaron last_name: Ray - first_name: Max full_name: Tschaikowski, Max last_name: Tschaikowski - first_name: Gerald full_name: Teschl, Gerald last_name: Teschl - first_name: Daniela full_name: Rus, Daniela last_name: Rus citation: ama: Hasani R, Lechner M, Amini A, et al. Closed-form continuous-time neural networks. Nature Machine Intelligence. 2022;4(11):992-1003. doi:10.1038/s42256-022-00556-7 apa: Hasani, R., Lechner, M., Amini, A., Liebenwein, L., Ray, A., Tschaikowski, M., … Rus, D. (2022). Closed-form continuous-time neural networks. Nature Machine Intelligence. Springer Nature. https://doi.org/10.1038/s42256-022-00556-7 chicago: Hasani, Ramin, Mathias Lechner, Alexander Amini, Lucas Liebenwein, Aaron Ray, Max Tschaikowski, Gerald Teschl, and Daniela Rus. “Closed-Form Continuous-Time Neural Networks.” Nature Machine Intelligence. Springer Nature, 2022. https://doi.org/10.1038/s42256-022-00556-7. ieee: R. Hasani et al., “Closed-form continuous-time neural networks,” Nature Machine Intelligence, vol. 4, no. 11. Springer Nature, pp. 992–1003, 2022. ista: Hasani R, Lechner M, Amini A, Liebenwein L, Ray A, Tschaikowski M, Teschl G, Rus D. 2022. Closed-form continuous-time neural networks. Nature Machine Intelligence. 4(11), 992–1003. mla: Hasani, Ramin, et al. “Closed-Form Continuous-Time Neural Networks.” Nature Machine Intelligence, vol. 4, no. 11, Springer Nature, 2022, pp. 992–1003, doi:10.1038/s42256-022-00556-7. short: R. Hasani, M. Lechner, A. Amini, L. Liebenwein, A. Ray, M. Tschaikowski, G. Teschl, D. Rus, Nature Machine Intelligence 4 (2022) 992–1003. date_created: 2023-01-12T12:07:21Z date_published: 2022-11-15T00:00:00Z date_updated: 2023-08-04T09:00:10Z day: '15' ddc: - '000' department: - _id: ToHe doi: 10.1038/s42256-022-00556-7 external_id: arxiv: - '2106.13898' isi: - '000884215600003' file: - access_level: open_access checksum: b4789122ce04bfb4ac042390f59aaa8b content_type: application/pdf creator: dernst date_created: 2023-01-24T09:49:44Z date_updated: 2023-01-24T09:49:44Z file_id: '12355' file_name: 2022_NatureMachineIntelligence_Hasani.pdf file_size: 3259553 relation: main_file success: 1 file_date_updated: 2023-01-24T09:49:44Z has_accepted_license: '1' intvolume: ' 4' isi: 1 issue: '11' keyword: - Artificial Intelligence - Computer Networks and Communications - Computer Vision and Pattern Recognition - Human-Computer Interaction - Software language: - iso: eng month: '11' oa: 1 oa_version: Published Version page: 992-1003 project: - _id: 25F42A32-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z211 name: The Wittgenstein Prize publication: Nature Machine Intelligence publication_identifier: issn: - 2522-5839 publication_status: published publisher: Springer Nature quality_controlled: '1' related_material: link: - relation: erratum url: https://doi.org/10.1038/s42256-022-00597-y scopus_import: '1' status: public title: Closed-form continuous-time neural networks 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: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 4 year: '2022' ...