--- _id: '9647' abstract: - lang: eng text: 'Gene expression is regulated by the set of transcription factors (TFs) that bind to the promoter. The ensuing regulating function is often represented as a combinational logic circuit, where output (gene expression) is determined by current input values (promoter bound TFs) only. However, the simultaneous arrival of TFs is a strong assumption, since transcription and translation of genes introduce intrinsic time delays and there is no global synchronisation among the arrival times of different molecular species at their targets. We present an experimentally implementable genetic circuit with two inputs and one output, which in the presence of small delays in input arrival, exhibits qualitatively distinct population-level phenotypes, over timescales that are longer than typical cell doubling times. From a dynamical systems point of view, these phenotypes represent long-lived transients: although they converge to the same value eventually, they do so after a very long time span. The key feature of this toy model genetic circuit is that, despite having only two inputs and one output, it is regulated by twenty-three distinct DNA-TF configurations, two of which are more stable than others (DNA looped states), one promoting and another blocking the expression of the output gene. Small delays in input arrival time result in a majority of cells in the population quickly reaching the stable state associated with the first input, while exiting of this stable state occurs at a slow timescale. In order to mechanistically model the behaviour of this genetic circuit, we used a rule-based modelling language, and implemented a grid-search to find parameter combinations giving rise to long-lived transients. Our analysis shows that in the absence of feedback, there exist path-dependent gene regulatory mechanisms based on the long timescale of transients. The behaviour of this toy model circuit suggests that gene regulatory networks can exploit event timing to create phenotypes, and it opens the possibility that they could use event timing to memorise events, without regulatory feedback. The model reveals the importance of (i) mechanistically modelling the transitions between the different DNA-TF states, and (ii) employing transient analysis thereof.' acknowledgement: 'Tatjana Petrov’s research was supported in part by SNSF Advanced Postdoctoral Mobility Fellowship grant number P300P2 161067, the Ministry of Science, Research and the Arts of the state of Baden-Wurttemberg, and the DFG Centre of Excellence 2117 ‘Centre for the Advanced Study of Collective Behaviour’ (ID: 422037984). Claudia Igler is the recipient of a DOC Fellowship of the Austrian Academy of Sciences. Thomas A. Henzinger’s research was supported in part by the Austrian Science Fund (FWF) under grant Z211-N23 (Wittgenstein Award).' article_processing_charge: No article_type: original author: - first_name: Tatjana full_name: Petrov, Tatjana last_name: Petrov - first_name: Claudia full_name: Igler, Claudia id: 46613666-F248-11E8-B48F-1D18A9856A87 last_name: Igler - first_name: Ali full_name: Sezgin, Ali id: 4C7638DA-F248-11E8-B48F-1D18A9856A87 last_name: Sezgin - 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: Calin C full_name: Guet, Calin C id: 47F8433E-F248-11E8-B48F-1D18A9856A87 last_name: Guet orcid: 0000-0001-6220-2052 citation: ama: Petrov T, Igler C, Sezgin A, Henzinger TA, Guet CC. Long lived transients in gene regulation. Theoretical Computer Science. 2021;893:1-16. doi:10.1016/j.tcs.2021.05.023 apa: Petrov, T., Igler, C., Sezgin, A., Henzinger, T. A., & Guet, C. C. (2021). Long lived transients in gene regulation. Theoretical Computer Science. Elsevier. https://doi.org/10.1016/j.tcs.2021.05.023 chicago: Petrov, Tatjana, Claudia Igler, Ali Sezgin, Thomas A Henzinger, and Calin C Guet. “Long Lived Transients in Gene Regulation.” Theoretical Computer Science. Elsevier, 2021. https://doi.org/10.1016/j.tcs.2021.05.023. ieee: T. Petrov, C. Igler, A. Sezgin, T. A. Henzinger, and C. C. Guet, “Long lived transients in gene regulation,” Theoretical Computer Science, vol. 893. Elsevier, pp. 1–16, 2021. ista: Petrov T, Igler C, Sezgin A, Henzinger TA, Guet CC. 2021. Long lived transients in gene regulation. Theoretical Computer Science. 893, 1–16. mla: Petrov, Tatjana, et al. “Long Lived Transients in Gene Regulation.” Theoretical Computer Science, vol. 893, Elsevier, 2021, pp. 1–16, doi:10.1016/j.tcs.2021.05.023. short: T. Petrov, C. Igler, A. Sezgin, T.A. Henzinger, C.C. Guet, Theoretical Computer Science 893 (2021) 1–16. date_created: 2021-07-11T22:01:18Z date_published: 2021-06-04T00:00:00Z date_updated: 2023-08-10T14:11:19Z day: '04' ddc: - '004' department: - _id: ToHe - _id: CaGu doi: 10.1016/j.tcs.2021.05.023 external_id: isi: - '000710180500002' file: - access_level: open_access checksum: d3aef34cfb13e53bba4cf44d01680793 content_type: application/pdf creator: dernst date_created: 2022-05-12T12:13:27Z date_updated: 2022-05-12T12:13:27Z file_id: '11364' file_name: 2021_TheoreticalComputerScience_Petrov.pdf file_size: 2566504 relation: main_file success: 1 file_date_updated: 2022-05-12T12:13:27Z has_accepted_license: '1' intvolume: ' 893' isi: 1 language: - iso: eng license: https://creativecommons.org/licenses/by-nc-nd/4.0/ month: '06' oa: 1 oa_version: Published Version page: 1-16 project: - _id: 25F42A32-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z211 name: The Wittgenstein Prize publication: Theoretical Computer Science publication_identifier: issn: - 0304-3975 publication_status: published publisher: Elsevier quality_controlled: '1' scopus_import: '1' status: public title: Long lived transients in gene regulation 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: journal_article user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 893 year: '2021' ... --- _id: '10108' abstract: - lang: eng text: We argue that the time is ripe to investigate differential monitoring, in which the specification of a program's behavior is implicitly given by a second program implementing the same informal specification. Similar ideas have been proposed before, and are currently implemented in restricted form for testing and specialized run-time analyses, aspects of which we combine. We discuss the challenges of implementing differential monitoring as a general-purpose, black-box run-time monitoring framework, and present promising results of a preliminary implementation, showing low monitoring overheads for diverse programs. acknowledgement: The authors would like to thank Borzoo Bonakdarpour, Derek Dreyer, Adrian Francalanza, Owolabi Legunsen, Mae Milano, Manuel Rigger, Cesar Sanchez, and the members of the IST Verification Seminar for their helpful comments and insights on various stages of this work, as well as the reviewers of RV’21 for their helpful suggestions on the actual paper. alternative_title: - LNCS article_processing_charge: No author: - first_name: Fabian full_name: Mühlböck, Fabian id: 6395C5F6-89DF-11E9-9C97-6BDFE5697425 last_name: Mühlböck orcid: 0000-0003-1548-0177 - 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: 'Mühlböck F, Henzinger TA. Differential monitoring. In: International Conference on Runtime Verification. Vol 12974. Cham: Springer Nature; 2021:231-243. doi:10.1007/978-3-030-88494-9_12' apa: 'Mühlböck, F., & Henzinger, T. A. (2021). Differential monitoring. In International Conference on Runtime Verification (Vol. 12974, pp. 231–243). Cham: Springer Nature. https://doi.org/10.1007/978-3-030-88494-9_12' chicago: 'Mühlböck, Fabian, and Thomas A Henzinger. “Differential Monitoring.” In International Conference on Runtime Verification, 12974:231–43. Cham: Springer Nature, 2021. https://doi.org/10.1007/978-3-030-88494-9_12.' ieee: F. Mühlböck and T. A. Henzinger, “Differential monitoring,” in International Conference on Runtime Verification, Virtual, 2021, vol. 12974, pp. 231–243. ista: 'Mühlböck F, Henzinger TA. 2021. Differential monitoring. International Conference on Runtime Verification. RV: Runtime Verification, LNCS, vol. 12974, 231–243.' mla: Mühlböck, Fabian, and Thomas A. Henzinger. “Differential Monitoring.” International Conference on Runtime Verification, vol. 12974, Springer Nature, 2021, pp. 231–43, doi:10.1007/978-3-030-88494-9_12. short: F. Mühlböck, T.A. Henzinger, in:, International Conference on Runtime Verification, Springer Nature, Cham, 2021, pp. 231–243. conference: end_date: 2021-10-14 location: Virtual name: 'RV: Runtime Verification' start_date: 2021-10-11 date_created: 2021-10-07T23:30:10Z date_published: 2021-10-06T00:00:00Z date_updated: 2023-08-14T07:20:30Z day: '06' ddc: - '005' department: - _id: ToHe doi: 10.1007/978-3-030-88494-9_12 external_id: isi: - '000719383800012' file: - access_level: open_access checksum: 554c7fdb259eda703a8b6328a6dad55a content_type: application/pdf creator: fmuehlbo date_created: 2021-10-07T23:32:18Z date_updated: 2021-10-07T23:32:18Z file_id: '10109' file_name: differentialmonitoring-cameraready-openaccess.pdf file_size: 350632 relation: main_file success: 1 file_date_updated: 2021-10-07T23:32:18Z has_accepted_license: '1' intvolume: ' 12974' isi: 1 keyword: - run-time verification - software engineering - implicit specification language: - iso: eng month: '10' oa: 1 oa_version: Preprint page: 231-243 place: Cham project: - _id: 25F42A32-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z211 name: The Wittgenstein Prize publication: International Conference on Runtime Verification publication_identifier: eisbn: - 978-3-030-88494-9 eissn: - 1611-3349 isbn: - 978-3-030-88493-2 issn: - 0302-9743 publication_status: published publisher: Springer Nature quality_controlled: '1' related_material: record: - id: '9946' relation: extended_version status: public scopus_import: '1' status: public title: Differential monitoring type: conference user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 12974 year: '2021' ... --- _id: '9946' abstract: - lang: eng text: We argue that the time is ripe to investigate differential monitoring, in which the specification of a program's behavior is implicitly given by a second program implementing the same informal specification. Similar ideas have been proposed before, and are currently implemented in restricted form for testing and specialized run-time analyses, aspects of which we combine. We discuss the challenges of implementing differential monitoring as a general-purpose, black-box run-time monitoring framework, and present promising results of a preliminary implementation, showing low monitoring overheads for diverse programs. acknowledgement: The authors would like to thank Borzoo Bonakdarpour, Derek Dreyer, Adrian Francalanza, Owolabi Legunsen, Matthew Milano, Manuel Rigger, Cesar Sanchez, and the members of the IST Verification Seminar for their helpful comments and insights on various stages of this work, as well as the reviewers of RV’21 for their helpful suggestions on the actual paper. alternative_title: - IST Austria Technical Report article_processing_charge: No author: - first_name: Fabian full_name: Mühlböck, Fabian id: 6395C5F6-89DF-11E9-9C97-6BDFE5697425 last_name: Mühlböck orcid: 0000-0003-1548-0177 - 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: Mühlböck F, Henzinger TA. Differential Monitoring. IST Austria; 2021. doi:10.15479/AT:ISTA:9946 apa: Mühlböck, F., & Henzinger, T. A. (2021). Differential monitoring. IST Austria. https://doi.org/10.15479/AT:ISTA:9946 chicago: Mühlböck, Fabian, and Thomas A Henzinger. Differential Monitoring. IST Austria, 2021. https://doi.org/10.15479/AT:ISTA:9946. ieee: F. Mühlböck and T. A. Henzinger, Differential monitoring. IST Austria, 2021. ista: Mühlböck F, Henzinger TA. 2021. Differential monitoring, IST Austria, 17p. mla: Mühlböck, Fabian, and Thomas A. Henzinger. Differential Monitoring. IST Austria, 2021, doi:10.15479/AT:ISTA:9946. short: F. Mühlböck, T.A. Henzinger, Differential Monitoring, IST Austria, 2021. date_created: 2021-08-20T20:00:37Z date_published: 2021-09-01T00:00:00Z date_updated: 2023-08-14T07:20:29Z day: '01' ddc: - '005' department: - _id: ToHe doi: 10.15479/AT:ISTA:9946 file: - access_level: open_access checksum: 0f9aafd59444cb6bdca6925d163ab946 content_type: application/pdf creator: fmuehlbo date_created: 2021-08-20T19:59:44Z date_updated: 2021-09-03T12:34:28Z file_id: '9948' file_name: differentialmonitoring-techreport.pdf file_size: '320453' relation: main_file file_date_updated: 2021-09-03T12:34:28Z has_accepted_license: '1' keyword: - run-time verification - software engineering - implicit specification language: - iso: eng month: '09' oa: 1 oa_version: Published Version page: '17' project: - _id: 25F42A32-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z211 name: The Wittgenstein Prize publication_identifier: issn: - 2664-1690 publication_status: published publisher: IST Austria related_material: record: - id: '9281' relation: other status: public - id: '10108' relation: shorter_version status: public status: public title: Differential monitoring type: technical_report user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9 year: '2021' ... --- _id: '10404' abstract: - lang: eng text: While convolutional neural networks (CNNs) have found wide adoption as state-of-the-art models for image-related tasks, their predictions are often highly sensitive to small input perturbations, which the human vision is robust against. This paper presents Perturber, a web-based application that allows users to instantaneously explore how CNN activations and predictions evolve when a 3D input scene is interactively perturbed. Perturber offers a large variety of scene modifications, such as camera controls, lighting and shading effects, background modifications, object morphing, as well as adversarial attacks, to facilitate the discovery of potential vulnerabilities. Fine-tuned model versions can be directly compared for qualitative evaluation of their robustness. Case studies with machine learning experts have shown that Perturber helps users to quickly generate hypotheses about model vulnerabilities and to qualitatively compare model behavior. Using quantitative analyses, we could replicate users’ insights with other CNN architectures and input images, yielding new insights about the vulnerability of adversarially trained models. acknowledgement: "We thank Robert Geirhos and Roland Zimmermann for their participation in the case study and valuable feedback, Chris Olah and Nick Cammarata for valuable discussions in the early phase of the project, as well as the Distill Slack workspace as a platform for discussions. M.L. is supported in part by the Austrian Science Fund (FWF) under grant Z211-N23 (Wittgenstein Award). J.B. is supported by the German Federal Ministry of Education and Research\r\n(BMBF) through the Competence Center for Machine Learning (TUE.AI, FKZ 01IS18039A) and the International Max Planck Research School for Intelligent Systems (IMPRS-IS). R.H. is partially supported by Boeing and Horizon-2020 ECSEL (grant 783163, iDev40).\r\n" article_processing_charge: No article_type: original author: - first_name: Stefan full_name: Sietzen, Stefan last_name: Sietzen - first_name: Mathias full_name: Lechner, Mathias id: 3DC22916-F248-11E8-B48F-1D18A9856A87 last_name: Lechner - first_name: Judy full_name: Borowski, Judy last_name: Borowski - first_name: Ramin full_name: Hasani, Ramin last_name: Hasani - first_name: Manuela full_name: Waldner, Manuela last_name: Waldner citation: ama: Sietzen S, Lechner M, Borowski J, Hasani R, Waldner M. Interactive analysis of CNN robustness. Computer Graphics Forum. 2021;40(7):253-264. doi:10.1111/cgf.14418 apa: Sietzen, S., Lechner, M., Borowski, J., Hasani, R., & Waldner, M. (2021). Interactive analysis of CNN robustness. Computer Graphics Forum. Wiley. https://doi.org/10.1111/cgf.14418 chicago: Sietzen, Stefan, Mathias Lechner, Judy Borowski, Ramin Hasani, and Manuela Waldner. “Interactive Analysis of CNN Robustness.” Computer Graphics Forum. Wiley, 2021. https://doi.org/10.1111/cgf.14418. ieee: S. Sietzen, M. Lechner, J. Borowski, R. Hasani, and M. Waldner, “Interactive analysis of CNN robustness,” Computer Graphics Forum, vol. 40, no. 7. Wiley, pp. 253–264, 2021. ista: Sietzen S, Lechner M, Borowski J, Hasani R, Waldner M. 2021. Interactive analysis of CNN robustness. Computer Graphics Forum. 40(7), 253–264. mla: Sietzen, Stefan, et al. “Interactive Analysis of CNN Robustness.” Computer Graphics Forum, vol. 40, no. 7, Wiley, 2021, pp. 253–64, doi:10.1111/cgf.14418. short: S. Sietzen, M. Lechner, J. Borowski, R. Hasani, M. Waldner, Computer Graphics Forum 40 (2021) 253–264. date_created: 2021-12-05T23:01:40Z date_published: 2021-11-27T00:00:00Z date_updated: 2023-08-14T13:11:42Z day: '27' department: - _id: ToHe doi: 10.1111/cgf.14418 external_id: arxiv: - '2110.07667' isi: - '000722952000024' intvolume: ' 40' isi: 1 issue: '7' language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/2110.07667 month: '11' oa: 1 oa_version: Preprint page: 253-264 project: - _id: 25F42A32-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z211 name: The Wittgenstein Prize publication: Computer Graphics Forum publication_identifier: eissn: - 1467-8659 issn: - 0167-7055 publication_status: published publisher: Wiley quality_controlled: '1' scopus_import: '1' status: public title: Interactive analysis of CNN robustness type: journal_article user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 40 year: '2021' ... --- _id: '10674' abstract: - lang: eng text: 'In two-player games on graphs, the players move a token through a graph to produce an infinite path, which determines the winner of the game. Such games are central in formal methods since they model the interaction between a non-terminating system and its environment. In bidding games the players bid for the right to move the token: in each round, the players simultaneously submit bids, and the higher bidder moves the token and pays the other player. Bidding games are known to have a clean and elegant mathematical structure that relies on the ability of the players to submit arbitrarily small bids. Many applications, however, require a fixed granularity for the bids, which can represent, for example, the monetary value expressed in cents. We study, for the first time, the combination of discrete-bidding and infinite-duration games. Our most important result proves that these games form a large determined subclass of concurrent games, where determinacy is the strong property that there always exists exactly one player who can guarantee winning the game. In particular, we show that, in contrast to non-discrete bidding games, the mechanism with which tied bids are resolved plays an important role in discrete-bidding games. We study several natural tie-breaking mechanisms and show that, while some do not admit determinacy, most natural mechanisms imply determinacy for every pair of initial budgets.' acknowledgement: "This research was supported in part by the Austrian Science Fund (FWF) under grants S11402-N23 (RiSE/SHiNE), Z211-N23 (Wittgenstein Award), and M 2369-N33 (Meitner fellowship).\r\n" article_processing_charge: No article_type: original author: - first_name: Milad full_name: Aghajohari, Milad last_name: Aghajohari - 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: Aghajohari M, Avni G, Henzinger TA. Determinacy in discrete-bidding infinite-duration games. Logical Methods in Computer Science. 2021;17(1):10:1-10:23. doi:10.23638/LMCS-17(1:10)2021 apa: Aghajohari, M., Avni, G., & Henzinger, T. A. (2021). Determinacy in discrete-bidding infinite-duration games. Logical Methods in Computer Science. International Federation for Computational Logic. https://doi.org/10.23638/LMCS-17(1:10)2021 chicago: Aghajohari, Milad, Guy Avni, and Thomas A Henzinger. “Determinacy in Discrete-Bidding Infinite-Duration Games.” Logical Methods in Computer Science. International Federation for Computational Logic, 2021. https://doi.org/10.23638/LMCS-17(1:10)2021. ieee: M. Aghajohari, G. Avni, and T. A. Henzinger, “Determinacy in discrete-bidding infinite-duration games,” Logical Methods in Computer Science, vol. 17, no. 1. International Federation for Computational Logic, p. 10:1-10:23, 2021. ista: Aghajohari M, Avni G, Henzinger TA. 2021. Determinacy in discrete-bidding infinite-duration games. Logical Methods in Computer Science. 17(1), 10:1-10:23. mla: Aghajohari, Milad, et al. “Determinacy in Discrete-Bidding Infinite-Duration Games.” Logical Methods in Computer Science, vol. 17, no. 1, International Federation for Computational Logic, 2021, p. 10:1-10:23, doi:10.23638/LMCS-17(1:10)2021. short: M. Aghajohari, G. Avni, T.A. Henzinger, Logical Methods in Computer Science 17 (2021) 10:1-10:23. date_created: 2022-01-25T16:32:13Z date_published: 2021-02-03T00:00:00Z date_updated: 2023-08-17T06:56:42Z day: '03' ddc: - '510' department: - _id: ToHe doi: 10.23638/LMCS-17(1:10)2021 external_id: arxiv: - '1905.03588' isi: - '000658724600010' file: - access_level: open_access checksum: b35586a50ed1ca8f44767de116d18d81 content_type: application/pdf creator: alisjak date_created: 2022-01-26T08:04:50Z date_updated: 2022-01-26T08:04:50Z file_id: '10690' file_name: 2021_LMCS_AGHAJOHAR.pdf file_size: 819878 relation: main_file success: 1 file_date_updated: 2022-01-26T08:04:50Z has_accepted_license: '1' intvolume: ' 17' isi: 1 issue: '1' keyword: - computer science - computer science and game theory - logic in computer science language: - iso: eng license: https://creativecommons.org/licenses/by/4.0/ month: '02' oa: 1 oa_version: Published Version page: 10:1-10:23 project: - _id: 264B3912-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: M02369 name: Formal Methods meets Algorithmic Game Theory - _id: 25F2ACDE-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: S11402-N23 name: Rigorous Systems Engineering - _id: 25F42A32-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z211 name: The Wittgenstein Prize publication: Logical Methods in Computer Science publication_identifier: eissn: - 1860-5974 publication_status: published publisher: International Federation for Computational Logic quality_controlled: '1' scopus_import: '1' status: public title: Determinacy in discrete-bidding infinite-duration games tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 17 year: '2021' ... --- _id: '10666' abstract: - lang: eng text: Adversarial training is an effective method to train deep learning models that are resilient to norm-bounded perturbations, with the cost of nominal performance drop. While adversarial training appears to enhance the robustness and safety of a deep model deployed in open-world decision-critical applications, counterintuitively, it induces undesired behaviors in robot learning settings. In this paper, we show theoretically and experimentally that neural controllers obtained via adversarial training are subjected to three types of defects, namely transient, systematic, and conditional errors. We first generalize adversarial training to a safety-domain optimization scheme allowing for more generic specifications. We then prove that such a learning process tends to cause certain error profiles. We support our theoretical results by a thorough experimental safety analysis in a robot-learning task. Our results suggest that adversarial training is not yet ready for robot learning. acknowledgement: M.L. and T.A.H. are supported in part by the Austrian Science Fund (FWF) under grant Z211-N23 (Wittgenstein Award). R.H. and D.R. are supported by Boeing and R.G. by Horizon-2020 ECSEL Project grant no. 783163 (iDev40). article_processing_charge: No author: - 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: Radu full_name: Grosu, Radu last_name: Grosu - 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, Hasani R, Grosu R, Rus D, Henzinger TA. Adversarial training is not ready for robot learning. In: 2021 IEEE International Conference on Robotics and Automation. ICRA. ; 2021:4140-4147. doi:10.1109/ICRA48506.2021.9561036' apa: Lechner, M., Hasani, R., Grosu, R., Rus, D., & Henzinger, T. A. (2021). Adversarial training is not ready for robot learning. In 2021 IEEE International Conference on Robotics and Automation (pp. 4140–4147). Xi’an, China. https://doi.org/10.1109/ICRA48506.2021.9561036 chicago: Lechner, Mathias, Ramin Hasani, Radu Grosu, Daniela Rus, and Thomas A Henzinger. “Adversarial Training Is Not Ready for Robot Learning.” In 2021 IEEE International Conference on Robotics and Automation, 4140–47. ICRA, 2021. https://doi.org/10.1109/ICRA48506.2021.9561036. ieee: M. Lechner, R. Hasani, R. Grosu, D. Rus, and T. A. Henzinger, “Adversarial training is not ready for robot learning,” in 2021 IEEE International Conference on Robotics and Automation, Xi’an, China, 2021, pp. 4140–4147. ista: 'Lechner M, Hasani R, Grosu R, Rus D, Henzinger TA. 2021. Adversarial training is not ready for robot learning. 2021 IEEE International Conference on Robotics and Automation. ICRA: International Conference on Robotics and AutomationICRA, 4140–4147.' mla: Lechner, Mathias, et al. “Adversarial Training Is Not Ready for Robot Learning.” 2021 IEEE International Conference on Robotics and Automation, 2021, pp. 4140–47, doi:10.1109/ICRA48506.2021.9561036. short: M. Lechner, R. Hasani, R. Grosu, D. Rus, T.A. Henzinger, in:, 2021 IEEE International Conference on Robotics and Automation, 2021, pp. 4140–4147. conference: end_date: 2021-06-05 location: Xi'an, China name: 'ICRA: International Conference on Robotics and Automation' start_date: 2021-05-30 date_created: 2022-01-25T15:44:54Z date_published: 2021-01-01T00:00:00Z date_updated: 2023-08-17T06:58:38Z ddc: - '000' department: - _id: GradSch - _id: ToHe doi: 10.1109/ICRA48506.2021.9561036 external_id: arxiv: - '2103.08187' isi: - '000765738803040' has_accepted_license: '1' isi: 1 language: - iso: eng license: https://creativecommons.org/licenses/by-nc-nd/3.0/ main_file_link: - open_access: '1' url: https://arxiv.org/abs/2103.08187 oa: 1 oa_version: None page: 4140-4147 project: - _id: 25F42A32-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z211 name: The Wittgenstein Prize publication: 2021 IEEE International Conference on Robotics and Automation publication_identifier: eisbn: - 978-1-7281-9077-8 eissn: - 2577-087X isbn: - 978-1-7281-9078-5 issn: - 1050-4729 publication_status: published quality_controlled: '1' related_material: record: - id: '11362' relation: dissertation_contains status: public series_title: ICRA status: public title: Adversarial training is not ready for robot learning tmp: image: /images/cc_by_nc_nd.png legal_code_url: https://creativecommons.org/licenses/by-nc-nd/3.0/legalcode name: Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0) short: CC BY-NC-ND (3.0) type: conference user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 year: '2021' ... --- _id: '10206' abstract: - lang: eng text: Neural-network classifiers achieve high accuracy when predicting the class of an input that they were trained to identify. Maintaining this accuracy in dynamic environments, where inputs frequently fall outside the fixed set of initially known classes, remains a challenge. The typical approach is to detect inputs from novel classes and retrain the classifier on an augmented dataset. However, not only the classifier but also the detection mechanism needs to adapt in order to distinguish between newly learned and yet unknown input classes. To address this challenge, we introduce an algorithmic framework for active monitoring of a neural network. A monitor wrapped in our framework operates in parallel with the neural network and interacts with a human user via a series of interpretable labeling queries for incremental adaptation. In addition, we propose an adaptive quantitative monitor to improve precision. An experimental evaluation on a diverse set of benchmarks with varying numbers of classes confirms the benefits of our active monitoring framework in dynamic scenarios. acknowledgement: We thank Christoph Lampert and Alex Greengold for fruitful discussions. This research was supported in part by the Simons Institute for the Theory of Computing, the Austrian Science Fund (FWF) under grant Z211-N23 (Wittgenstein Award), and the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 754411. alternative_title: - LNCS article_processing_charge: No author: - first_name: Anna full_name: Lukina, Anna id: CBA4D1A8-0FE8-11E9-BDE6-07BFE5697425 last_name: Lukina - first_name: Christian full_name: Schilling, Christian id: 3A2F4DCE-F248-11E8-B48F-1D18A9856A87 last_name: Schilling orcid: 0000-0003-3658-1065 - 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: 'Lukina A, Schilling C, Henzinger TA. Into the unknown: active monitoring of neural networks. In: 21st International Conference on Runtime Verification. Vol 12974. Cham: Springer Nature; 2021:42-61. doi:10.1007/978-3-030-88494-9_3' apa: 'Lukina, A., Schilling, C., & Henzinger, T. A. (2021). Into the unknown: active monitoring of neural networks. In 21st International Conference on Runtime Verification (Vol. 12974, pp. 42–61). Cham: Springer Nature. https://doi.org/10.1007/978-3-030-88494-9_3' chicago: 'Lukina, Anna, Christian Schilling, and Thomas A Henzinger. “Into the Unknown: Active Monitoring of Neural Networks.” In 21st International Conference on Runtime Verification, 12974:42–61. Cham: Springer Nature, 2021. https://doi.org/10.1007/978-3-030-88494-9_3.' ieee: 'A. Lukina, C. Schilling, and T. A. Henzinger, “Into the unknown: active monitoring of neural networks,” in 21st International Conference on Runtime Verification, Virtual, 2021, vol. 12974, pp. 42–61.' ista: 'Lukina A, Schilling C, Henzinger TA. 2021. Into the unknown: active monitoring of neural networks. 21st International Conference on Runtime Verification. RV: Runtime Verification, LNCS, vol. 12974, 42–61.' mla: 'Lukina, Anna, et al. “Into the Unknown: Active Monitoring of Neural Networks.” 21st International Conference on Runtime Verification, vol. 12974, Springer Nature, 2021, pp. 42–61, doi:10.1007/978-3-030-88494-9_3.' short: A. Lukina, C. Schilling, T.A. Henzinger, in:, 21st International Conference on Runtime Verification, Springer Nature, Cham, 2021, pp. 42–61. conference: end_date: 2021-10-14 location: Virtual name: 'RV: Runtime Verification' start_date: 2021-10-11 date_created: 2021-10-31T23:01:31Z date_published: 2021-10-06T00:00:00Z date_updated: 2024-01-30T12:06:56Z day: '06' department: - _id: ToHe doi: 10.1007/978-3-030-88494-9_3 ec_funded: 1 external_id: arxiv: - '2009.06429' isi: - '000719383800003' isi: 1 keyword: - monitoring - neural networks - novelty detection language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/2009.06429 month: '10' oa: 1 oa_version: Preprint page: 42-61 place: Cham project: - _id: 260C2330-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '754411' name: ISTplus - Postdoctoral Fellowships - _id: 25F42A32-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z211 name: The Wittgenstein Prize publication: 21st International Conference on Runtime Verification publication_identifier: eisbn: - 978-3-030-88494-9 eissn: - 1611-3349 isbn: - 9-783-0308-8493-2 issn: - 0302-9743 publication_status: published publisher: Springer Nature quality_controlled: '1' related_material: record: - id: '13234' relation: extended_version status: public scopus_import: '1' status: public title: 'Into the unknown: active monitoring of neural networks' type: conference user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: '12974 ' year: '2021' ... --- _id: '10673' abstract: - lang: eng text: We propose a neural information processing system obtained by re-purposing the function of a biological neural circuit model to govern simulated and real-world control tasks. Inspired by the structure of the nervous system of the soil-worm, C. elegans, we introduce ordinary neural circuits (ONCs), defined as the model of biological neural circuits reparameterized for the control of alternative tasks. We first demonstrate that ONCs realize networks with higher maximum flow compared to arbitrary wired networks. We then learn instances of ONCs to control a series of robotic tasks, including the autonomous parking of a real-world rover robot. For reconfiguration of the purpose of the neural circuit, we adopt a search-based optimization algorithm. Ordinary neural circuits perform on par and, in some cases, significantly surpass the performance of contemporary deep learning models. ONC networks are compact, 77% sparser than their counterpart neural controllers, and their neural dynamics are fully interpretable at the cell-level. acknowledgement: "RH and RG are partially supported by Horizon-2020 ECSEL Project grant No. 783163 (iDev40), Productive 4.0, and ATBMBFW CPS-IoT Ecosystem. ML was supported in part by the Austrian Science Fund (FWF) under grant Z211-N23\r\n(Wittgenstein Award). AA is supported by the National Science Foundation (NSF) Graduate Research Fellowship\r\nProgram. RH and DR are partially supported by The Boeing Company and JP Morgan Chase. This research work is\r\npartially drawn from the PhD dissertation of RH.\r\n" alternative_title: - PMLR article_processing_charge: No 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: Daniela full_name: Rus, Daniela last_name: Rus - first_name: Radu full_name: Grosu, Radu last_name: Grosu citation: ama: 'Hasani R, Lechner M, Amini A, Rus D, Grosu R. A natural lottery ticket winner: Reinforcement learning with ordinary neural circuits. In: Proceedings of the 37th International Conference on Machine Learning. PMLR. ; 2020:4082-4093.' apa: 'Hasani, R., Lechner, M., Amini, A., Rus, D., & Grosu, R. (2020). A natural lottery ticket winner: Reinforcement learning with ordinary neural circuits. In Proceedings of the 37th International Conference on Machine Learning (pp. 4082–4093). Virtual.' chicago: 'Hasani, Ramin, Mathias Lechner, Alexander Amini, Daniela Rus, and Radu Grosu. “A Natural Lottery Ticket Winner: Reinforcement Learning with Ordinary Neural Circuits.” In Proceedings of the 37th International Conference on Machine Learning, 4082–93. PMLR, 2020.' ieee: 'R. Hasani, M. Lechner, A. Amini, D. Rus, and R. Grosu, “A natural lottery ticket winner: Reinforcement learning with ordinary neural circuits,” in Proceedings of the 37th International Conference on Machine Learning, Virtual, 2020, pp. 4082–4093.' ista: 'Hasani R, Lechner M, Amini A, Rus D, Grosu R. 2020. A natural lottery ticket winner: Reinforcement learning with ordinary neural circuits. Proceedings of the 37th International Conference on Machine Learning. ML: Machine LearningPMLR, PMLR, , 4082–4093.' mla: 'Hasani, Ramin, et al. “A Natural Lottery Ticket Winner: Reinforcement Learning with Ordinary Neural Circuits.” Proceedings of the 37th International Conference on Machine Learning, 2020, pp. 4082–93.' short: R. Hasani, M. Lechner, A. Amini, D. Rus, R. Grosu, in:, Proceedings of the 37th International Conference on Machine Learning, 2020, pp. 4082–4093. conference: end_date: 2020-07-18 location: Virtual name: 'ML: Machine Learning' start_date: 2020-07-12 date_created: 2022-01-25T15:50:34Z date_published: 2020-01-01T00:00:00Z date_updated: 2022-01-26T11:14:27Z ddc: - '000' department: - _id: GradSch - _id: ToHe file: - access_level: open_access checksum: c9a4a29161777fc1a89ef451c040e3b1 content_type: application/pdf creator: cchlebak date_created: 2022-01-26T11:08:51Z date_updated: 2022-01-26T11:08:51Z file_id: '10691' file_name: 2020_PMLR_Hasani.pdf file_size: 2329798 relation: main_file success: 1 file_date_updated: 2022-01-26T11:08:51Z has_accepted_license: '1' language: - iso: eng main_file_link: - open_access: '1' url: http://proceedings.mlr.press/v119/hasani20a.html oa: 1 oa_version: Published Version page: 4082-4093 project: - _id: 25F42A32-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z211 name: The Wittgenstein Prize publication: Proceedings of the 37th International Conference on Machine Learning publication_identifier: issn: - 2640-3498 publication_status: published quality_controlled: '1' scopus_import: '1' series_title: PMLR status: public title: 'A natural lottery ticket winner: Reinforcement learning with ordinary neural circuits' tmp: image: /images/cc_by_nc_nd.png legal_code_url: https://creativecommons.org/licenses/by-nc-nd/3.0/legalcode name: Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0) short: CC BY-NC-ND (3.0) type: conference user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9 year: '2020' ... --- _id: '7348' abstract: - lang: eng text: 'The monitoring of event frequencies can be used to recognize behavioral anomalies, to identify trends, and to deduce or discard hypotheses about the underlying system. For example, the performance of a web server may be monitored based on the ratio of the total count of requests from the least and most active clients. Exact frequency monitoring, however, can be prohibitively expensive; in the above example it would require as many counters as there are clients. In this paper, we propose the efficient probabilistic monitoring of common frequency properties, including the mode (i.e., the most common event) and the median of an event sequence. We define a logic to express composite frequency properties as a combination of atomic frequency properties. Our main contribution is an algorithm that, under suitable probabilistic assumptions, can be used to monitor these important frequency properties with four counters, independent of the number of different events. Our algorithm samples longer and longer subwords of an infinite event sequence. We prove the almost-sure convergence of our algorithm by generalizing ergodic theory from increasing-length prefixes to increasing-length subwords of an infinite sequence. A similar algorithm could be used to learn a connected Markov chain of a given structure from observing its outputs, to arbitrary precision, for a given confidence. ' alternative_title: - LIPIcs article_number: '20' article_processing_charge: No author: - 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: Bernhard full_name: Kragl, Bernhard id: 320FC952-F248-11E8-B48F-1D18A9856A87 last_name: Kragl orcid: 0000-0001-7745-9117 citation: ama: 'Ferrere T, Henzinger TA, Kragl B. Monitoring event frequencies. In: 28th EACSL Annual Conference on Computer Science Logic. Vol 152. Schloss Dagstuhl - Leibniz-Zentrum für Informatik; 2020. doi:10.4230/LIPIcs.CSL.2020.20' apa: 'Ferrere, T., Henzinger, T. A., & Kragl, B. (2020). Monitoring event frequencies. In 28th EACSL Annual Conference on Computer Science Logic (Vol. 152). Barcelona, Spain: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.CSL.2020.20' chicago: Ferrere, Thomas, Thomas A Henzinger, and Bernhard Kragl. “Monitoring Event Frequencies.” In 28th EACSL Annual Conference on Computer Science Logic, Vol. 152. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2020. https://doi.org/10.4230/LIPIcs.CSL.2020.20. ieee: T. Ferrere, T. A. Henzinger, and B. Kragl, “Monitoring event frequencies,” in 28th EACSL Annual Conference on Computer Science Logic, Barcelona, Spain, 2020, vol. 152. ista: 'Ferrere T, Henzinger TA, Kragl B. 2020. Monitoring event frequencies. 28th EACSL Annual Conference on Computer Science Logic. CSL: Computer Science Logic, LIPIcs, vol. 152, 20.' mla: Ferrere, Thomas, et al. “Monitoring Event Frequencies.” 28th EACSL Annual Conference on Computer Science Logic, vol. 152, 20, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2020, doi:10.4230/LIPIcs.CSL.2020.20. short: T. Ferrere, T.A. Henzinger, B. Kragl, in:, 28th EACSL Annual Conference on Computer Science Logic, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2020. conference: end_date: 2020-01-16 location: Barcelona, Spain name: 'CSL: Computer Science Logic' start_date: 2020-01-13 date_created: 2020-01-21T11:22:21Z date_published: 2020-01-15T00:00:00Z date_updated: 2021-01-12T08:13:12Z day: '15' ddc: - '000' department: - _id: ToHe doi: 10.4230/LIPIcs.CSL.2020.20 external_id: arxiv: - '1910.06097' file: - access_level: open_access checksum: b9a691d658d075c6369d3304d17fb818 content_type: application/pdf creator: bkragl date_created: 2020-01-21T11:21:04Z date_updated: 2020-07-14T12:47:56Z file_id: '7349' file_name: main.pdf file_size: 617206 relation: main_file file_date_updated: 2020-07-14T12:47:56Z has_accepted_license: '1' intvolume: ' 152' language: - iso: eng month: '01' oa: 1 oa_version: Published Version project: - _id: 25F2ACDE-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: S11402-N23 name: Rigorous Systems Engineering - _id: 25F42A32-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z211 name: The Wittgenstein Prize publication: 28th EACSL Annual Conference on Computer Science Logic publication_identifier: isbn: - '9783959771320' issn: - 1868-8969 publication_status: published publisher: Schloss Dagstuhl - Leibniz-Zentrum für Informatik quality_controlled: '1' scopus_import: 1 status: public title: Monitoring event frequencies 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: 152 year: '2020' ... --- _id: '8572' abstract: - lang: eng text: 'We present the results of the ARCH 2020 friendly competition for formal verification of continuous and hybrid systems with linear continuous dynamics. In its fourth edition, eight tools have been applied to solve eight different benchmark problems in the category for linear continuous dynamics (in alphabetical order): CORA, C2E2, HyDRA, Hylaa, Hylaa-Continuous, JuliaReach, SpaceEx, and XSpeed. This report is a snapshot of the current landscape of tools and the types of benchmarks they are particularly suited for. Due to the diversity of problems, we are not ranking tools, yet the presented results provide one of the most complete assessments of tools for the safety verification of continuous and hybrid systems with linear continuous dynamics up to this date.' acknowledgement: "The authors gratefully acknowledge financial support by the European Commission project\r\njustITSELF under grant number 817629, by the Austrian Science Fund (FWF) under grant\r\nZ211-N23 (Wittgenstein Award), by the European Union’s Horizon 2020 research and innovation programme under the Marie Sk lodowska-Curie grant agreement No. 754411, and by the\r\nScience and Engineering Research Board (SERB) project with file number IMP/2018/000523.\r\nThis material is based upon work supported by the Air Force Office of Scientific Research under\r\naward number FA9550-19-1-0288. Any opinions, finding, and conclusions or recommendations\r\nexpressed in this material are those of the author(s) and do not necessarily reflect the views of\r\nthe United States Air Force." article_processing_charge: No author: - first_name: Matthias full_name: Althoff, Matthias last_name: Althoff - first_name: Stanley full_name: Bak, Stanley last_name: Bak - first_name: Zongnan full_name: Bao, Zongnan last_name: Bao - first_name: Marcelo full_name: Forets, Marcelo last_name: Forets - first_name: Goran full_name: Frehse, Goran last_name: Frehse - first_name: Daniel full_name: Freire, Daniel last_name: Freire - first_name: Niklas full_name: Kochdumper, Niklas last_name: Kochdumper - first_name: Yangge full_name: Li, Yangge last_name: Li - first_name: Sayan full_name: Mitra, Sayan last_name: Mitra - first_name: Rajarshi full_name: Ray, Rajarshi last_name: Ray - first_name: Christian full_name: Schilling, Christian id: 3A2F4DCE-F248-11E8-B48F-1D18A9856A87 last_name: Schilling orcid: 0000-0003-3658-1065 - first_name: Stefan full_name: Schupp, Stefan last_name: Schupp - first_name: Mark full_name: Wetzlinger, Mark last_name: Wetzlinger citation: ama: 'Althoff M, Bak S, Bao Z, et al. ARCH-COMP20 Category Report: Continuous and hybrid systems with linear dynamics. In: EPiC Series in Computing. Vol 74. EasyChair; 2020:16-48. doi:10.29007/7dt2' apa: 'Althoff, M., Bak, S., Bao, Z., Forets, M., Frehse, G., Freire, D., … Wetzlinger, M. (2020). ARCH-COMP20 Category Report: Continuous and hybrid systems with linear dynamics. In EPiC Series in Computing (Vol. 74, pp. 16–48). EasyChair. https://doi.org/10.29007/7dt2' chicago: 'Althoff, Matthias, Stanley Bak, Zongnan Bao, Marcelo Forets, Goran Frehse, Daniel Freire, Niklas Kochdumper, et al. “ARCH-COMP20 Category Report: Continuous and Hybrid Systems with Linear Dynamics.” In EPiC Series in Computing, 74:16–48. EasyChair, 2020. https://doi.org/10.29007/7dt2.' ieee: 'M. Althoff et al., “ARCH-COMP20 Category Report: Continuous and hybrid systems with linear dynamics,” in EPiC Series in Computing, 2020, vol. 74, pp. 16–48.' ista: 'Althoff M, Bak S, Bao Z, Forets M, Frehse G, Freire D, Kochdumper N, Li Y, Mitra S, Ray R, Schilling C, Schupp S, Wetzlinger M. 2020. ARCH-COMP20 Category Report: Continuous and hybrid systems with linear dynamics. EPiC Series in Computing. ARCH: International Workshop on Applied Verification on Continuous and Hybrid Systems vol. 74, 16–48.' mla: 'Althoff, Matthias, et al. “ARCH-COMP20 Category Report: Continuous and Hybrid Systems with Linear Dynamics.” EPiC Series in Computing, vol. 74, EasyChair, 2020, pp. 16–48, doi:10.29007/7dt2.' short: M. Althoff, S. Bak, Z. Bao, M. Forets, G. Frehse, D. Freire, N. Kochdumper, Y. Li, S. Mitra, R. Ray, C. Schilling, S. Schupp, M. Wetzlinger, in:, EPiC Series in Computing, EasyChair, 2020, pp. 16–48. conference: end_date: 2020-07-12 name: 'ARCH: International Workshop on Applied Verification on Continuous and Hybrid Systems' start_date: 2020-07-12 date_created: 2020-09-26T14:49:43Z date_published: 2020-09-25T00:00:00Z date_updated: 2021-01-12T08:20:06Z day: '25' department: - _id: ToHe doi: 10.29007/7dt2 ec_funded: 1 intvolume: ' 74' language: - iso: eng main_file_link: - open_access: '1' url: https://easychair.org/publications/download/DRpS month: '09' oa: 1 oa_version: Published Version page: 16-48 project: - _id: 25C5A090-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z00312 name: The Wittgenstein Prize - _id: 260C2330-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '754411' name: ISTplus - Postdoctoral Fellowships publication: EPiC Series in Computing publication_status: published publisher: EasyChair quality_controlled: '1' status: public title: 'ARCH-COMP20 Category Report: Continuous and hybrid systems with linear dynamics' type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 74 year: '2020' ...