{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,17]],"date-time":"2026-07-17T11:06:38Z","timestamp":1784286398744,"version":"3.55.0"},"publisher-location":"Cham","reference-count":49,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783032323569","type":"print"},{"value":"9783032323576","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,7,18]],"date-time":"2026-07-18T00:00:00Z","timestamp":1784332800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,7,18]],"date-time":"2026-07-18T00:00:00Z","timestamp":1784332800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2027]]},"DOI":"10.1007\/978-3-032-32357-6_4","type":"book-chapter","created":{"date-parts":[[2026,7,17]],"date-time":"2026-07-17T10:36:23Z","timestamp":1784284583000},"page":"73-98","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Certified Neural Approximations of\u00a0Nonlinear Dynamics"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2243-0445","authenticated-orcid":false,"given":"Frederik Baymler","family":"Mathiesen","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4244-8623","authenticated-orcid":false,"given":"Nikolaus","family":"Vertovec","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1161-0336","authenticated-orcid":false,"given":"Francesco","family":"Fabiano","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1190-6097","authenticated-orcid":false,"given":"Luca","family":"Laurenti","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5627-9093","authenticated-orcid":false,"given":"Alessandro","family":"Abate","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,7,18]]},"reference":[{"key":"4_CR1","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"270","DOI":"10.1007\/978-3-319-96145-3_15","volume-title":"Computer Aided Verification","author":"A Abate","year":"2018","unstructured":"Abate, A., David, C., Kesseli, P., Kroening, D., Polgreen, E.: Counterexample guided inductive synthesis modulo theories. In: Chockler, H., Weissenbacher, G. (eds.) CAV 2018. LNCS, vol. 10981, pp. 270\u2013288. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-96145-3_15"},{"key":"4_CR2","doi-asserted-by":"crossref","unstructured":"Abate, A., Edwards, A., Giacobbe, M.: Neural abstractions. In: Proceedings of the 36th International Conference on Neural Information Processing Systems. NIPS \u201922. Curran Associates Inc., Red Hook (2022)","DOI":"10.52202\/068431-1917"},{"key":"4_CR3","doi-asserted-by":"crossref","unstructured":"Althoff, M., Stursberg, O., Buss, M.: Reachability analysis of nonlinear systems with uncertain parameters using conservative linearization. In: Proceedings of the 47th IEEE Conference on Decision and Control (CDC), pp. 4042\u20134048. IEEE (2008)","DOI":"10.1109\/CDC.2008.4738704"},{"key":"4_CR4","unstructured":"Alur, R.: Principles of Cyber-Physical Systems. MIT Press, Cambridge (2015)"},{"issue":"7","key":"4_CR5","doi-asserted-by":"publisher","first-page":"451","DOI":"10.1007\/s00236-006-0035-7","volume":"43","author":"E Asarin","year":"2007","unstructured":"Asarin, E., Dang, T., Girard, A.: Hybridization methods for the analysis of nonlinear systems. Acta Informatica 43(7), 451\u2013476 (2007)","journal-title":"Acta Informatica"},{"key":"4_CR6","unstructured":"Baier, C., Katoen, J.P.: Principles of Model Checking. MIT Press, Cambridge (2008)"},{"key":"4_CR7","doi-asserted-by":"crossref","unstructured":"Bak, S., Bogomolov, S., Henzinger, T.A., Johnson, T.T., Prakash, P.: Scalable static hybridization methods for analysis of nonlinear systems. In: Proceedings of the 19th International Conference on Hybrid Systems: Computation and Control (HSCC), pp. 155\u2013164. ACM (2016)","DOI":"10.1145\/2883817.2883837"},{"issue":"32","key":"4_CR8","doi-asserted-by":"publisher","first-page":"15849","DOI":"10.1073\/pnas.1903070116","volume":"116","author":"M Belkin","year":"2019","unstructured":"Belkin, M., Hsu, D., Ma, S., Mandal, S.: Reconciling modern machine-learning practice and the classical bias-variance trade-off. Proc. Natl. Acad. Sci. 116(32), 15849\u201315854 (2019). https:\/\/doi.org\/10.1073\/pnas.1903070116","journal-title":"Proc. Natl. Acad. Sci."},{"key":"4_CR9","unstructured":"Brix, C., Bak, S., Johnson, T.T., Wu, H.: The fifth international verification of neural networks competition (VNN-COMP 2024): Summary and results. CoRR arxiv:2412.19985 (2024)"},{"issue":"2","key":"4_CR10","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0150171","volume":"11","author":"SL Brunton","year":"2016","unstructured":"Brunton, S.L., Brunton, B.W., Proctor, J.L., Kutz, J.N.: Koopman invariant subspaces and finite linear representations of nonlinear dynamical systems for control. PLoS ONE 11(2), e0150171 (2016). https:\/\/doi.org\/10.1371\/journal.pone.0150171","journal-title":"PLoS ONE"},{"issue":"2","key":"4_CR11","doi-asserted-by":"publisher","first-page":"229","DOI":"10.1137\/21M1401243","volume":"64","author":"SL Brunton","year":"2022","unstructured":"Brunton, S.L., Budi\u0161i\u0107, M., Kaiser, E., Kutz, J.N.: Modern koopman theory for dynamical systems. SIAM Rev. 64(2), 229\u2013340 (2022). https:\/\/doi.org\/10.1137\/21M1401243","journal-title":"SIAM Rev."},{"key":"4_CR12","unstructured":"Clarke, E.M., Grumberg, O., Kroening, D., Peled, D.A., Veith, H.: Model Checking, 2nd edn. MIT Press, Cambridge (2018)"},{"key":"4_CR13","doi-asserted-by":"crossref","unstructured":"Dang, T., Maler, O., Testylier, R.: Accurate hybridization of nonlinear systems. In: Proceedings of the 13th ACM International Conference on Hybrid Systems: Computation and Control (HSCC), pp. 11\u201320. ACM (2010)","DOI":"10.1145\/1755952.1755956"},{"issue":"1","key":"4_CR14","doi-asserted-by":"publisher","first-page":"42","DOI":"10.1287\/opre.50.1.42.17798","volume":"50","author":"GB Dantzig","year":"2002","unstructured":"Dantzig, G.B.: Linear programming. Oper. Res. 50(1), 42\u201347 (2002)","journal-title":"Oper. Res."},{"issue":"1","key":"4_CR15","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1109\/JPROC.2011.2160929","volume":"100","author":"P Derler","year":"2012","unstructured":"Derler, P., Lee, E.A., Sangiovanni Vincentelli, A.: Modeling cyber-physical systems. Proc. IEEE 100(1), 13\u201328 (2012). https:\/\/doi.org\/10.1109\/JPROC.2011.2160929","journal-title":"Proc. IEEE"},{"key":"4_CR16","unstructured":"Dey, S., Davis, E.W.: Dlkoopman: a deep learning software package for Koopman theory. In: Matni, N., Morari, M., Pappas, G.J. (eds.) Proceedings of The 5th Annual Learning for Dynamics and Control Conference. Proceedings of Machine Learning Research, vol.\u00a0211, pp. 1467\u20131479. PMLR (2023)"},{"key":"4_CR17","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"258","DOI":"10.1007\/978-3-540-31954-2_17","volume-title":"Hybrid Systems: Computation and Control","author":"G Frehse","year":"2005","unstructured":"Frehse, G.: PHAVer: algorithmic verification of hybrid systems past HyTech. In: Morari, M., Thiele, L. (eds.) HSCC 2005. LNCS, vol. 3414, pp. 258\u2013273. Springer, Heidelberg (2005). https:\/\/doi.org\/10.1007\/978-3-540-31954-2_17"},{"issue":"3\u20134","key":"4_CR18","doi-asserted-by":"publisher","first-page":"209","DOI":"10.3233\/sat190012","volume":"1","author":"M Fr\u00e4nzle","year":"2007","unstructured":"Fr\u00e4nzle, M., Herde, C., Teige, T., Ratschan, S., Schubert, T.: Efficient solving of large non-linear arithmetic constraint systems with complex Boolean structure1. J. Satisfiabil. Boolean Model. Comput. 1(3\u20134), 209\u2013236 (2007). https:\/\/doi.org\/10.3233\/sat190012","journal-title":"J. Satisfiabil. Boolean Model. Comput."},{"key":"4_CR19","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"208","DOI":"10.1007\/978-3-642-38574-2_14","volume-title":"Automated Deduction \u2013 CADE-24","author":"S Gao","year":"2013","unstructured":"Gao, S., Kong, S., Clarke, E.M.: dReal: an SMT solver for nonlinear theories over the reals. In: Bonacina, M.P. (ed.) CADE 2013. LNCS (LNAI), vol. 7898, pp. 208\u2013214. Springer, Heidelberg (2013). https:\/\/doi.org\/10.1007\/978-3-642-38574-2_14"},{"key":"4_CR20","doi-asserted-by":"crossref","unstructured":"Garc\u00eda\u00a0Soto, M., Prabhakar, P.: Hybridization for stability verification of nonlinear switched systems. In: Proceedings of the 41st IEEE Real-Time Systems Symposium (RTSS), pp. 244\u2013256. IEEE (2020)","DOI":"10.1109\/RTSS49844.2020.00031"},{"issue":"6","key":"4_CR21","doi-asserted-by":"publisher","first-page":"1789","DOI":"10.1007\/s11263-021-01453-z","volume":"129","author":"J Gou","year":"2021","unstructured":"Gou, J., Yu, B., Maybank, S.J., Tao, D.: Knowledge distillation: a survey. Int. J. Comput. Vision 129(6), 1789\u20131819 (2021)","journal-title":"Int. J. Comput. Vision"},{"key":"4_CR22","doi-asserted-by":"publisher","DOI":"10.1016\/j.cam.2023.115667","volume":"441","author":"A Goujon","year":"2024","unstructured":"Goujon, A., Etemadi, A., Unser, M.: On the number of regions of piecewise linear neural networks. J. Comput. Appl. Math. 441, 115667 (2024). https:\/\/doi.org\/10.1016\/j.cam.2023.115667","journal-title":"J. Comput. Appl. Math."},{"issue":"2","key":"4_CR23","doi-asserted-by":"publisher","first-page":"391","DOI":"10.3934\/jcd.2014.1.391","volume":"1","author":"JH Tu","year":"2014","unstructured":"Tu, J.H., Rowley, C.W., Luchtenburg, D.M., Brunton, S.L., Nathan Kutz, J.: On dynamic mode decomposition: theory and applications. J. Comput. Dyn. 1(2), 391\u2013421 (2014). https:\/\/doi.org\/10.3934\/jcd.2014.1.391","journal-title":"J. Comput. Dyn."},{"key":"4_CR24","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"377","DOI":"10.1007\/BFb0020961","volume-title":"Hybrid Systems III","author":"TA Henzinger","year":"1996","unstructured":"Henzinger, T.A., Wong-Toi, H.: Linear phase-portrait approximations for nonlinear hybrid systems. In: Alur, R., Henzinger, T.A., Sontag, E.D. (eds.) HS 1995. LNCS, vol. 1066, pp. 377\u2013388. Springer, Heidelberg (1996). https:\/\/doi.org\/10.1007\/BFb0020961"},{"key":"4_CR25","doi-asserted-by":"publisher","unstructured":"Huang, C., Fan, J., Chen, X., Li, W., Zhu, Q.: Polar: a polynomial arithmetic framework for verifying neural-network controlled systems. In: Automated Technology for Verification and Analysis: 20th International Symposium, ATVA 2022, Virtual Event, 25\u201328 October 2022, Proceedings, pp. 414\u2013430. Springer, Heidelberg (2022). https:\/\/doi.org\/10.1007\/978-3-031-19992-9_27","DOI":"10.1007\/978-3-031-19992-9_27"},{"key":"4_CR26","doi-asserted-by":"publisher","unstructured":"Huang, C., Fan, J., Li, W., Chen, X., Zhu, Q.: Reachnn: reachability analysis of neural-network controlled systems. ACM Trans. Embed. Comput. Syst. 18(5s) (2019). https:\/\/doi.org\/10.1145\/3358228","DOI":"10.1145\/3358228"},{"key":"4_CR27","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"249","DOI":"10.1007\/978-3-030-81685-8_11","volume-title":"Computer Aided Verification","author":"R Ivanov","year":"2021","unstructured":"Ivanov, R., Carpenter, T., Weimer, J., Alur, R., Pappas, G., Lee, I.: Verisig 2.0: verification of neural network controllers using taylor model preconditioning. In: Silva, A., Leino, K.R.M. (eds.) CAV 2021. LNCS, vol. 12759, pp. 249\u2013262. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-81685-8_11"},{"key":"4_CR28","unstructured":"Jacot, A., Gabriel, F., Hongler, C.: Neural tangent kernel: convergence and generalization in neural networks. In: Proceedings of the 32nd International Conference on Neural Information Processing Systems, NIPS\u201918, pp. 8580\u20138589. Curran Associates Inc., Red Hook (2018)"},{"key":"4_CR29","unstructured":"Joldes, M.M.: Rigorous Polynomial Approximations and Applications. Theses, Ecole normale sup\u00e9rieure de lyon - ENS LYON (2011)"},{"key":"4_CR30","volume-title":"Nonlinear Systems","author":"HK Khalil","year":"2002","unstructured":"Khalil, H.K.: Nonlinear Systems, 3rd edn. Prentice Hall, Upper Saddle River (2002)","edition":"3"},{"key":"4_CR31","doi-asserted-by":"crossref","unstructured":"Koopman, B.O.: Hamiltonian systems and transformations in hilbert space. Proc. Natl. Acad. Sci. USA 17(5), 315\u2013318 (1931). http:\/\/www.jstor.org\/stable\/86114","DOI":"10.1073\/pnas.17.5.315"},{"key":"4_CR32","doi-asserted-by":"publisher","first-page":"149","DOI":"10.1016\/j.automatica.2018.03.046","volume":"93","author":"M Korda","year":"2018","unstructured":"Korda, M., Mezi\u0107, I.: Linear predictors for nonlinear dynamical systems: Koopman operator meets model predictive control. Automatica 93, 149\u2013160 (2018). https:\/\/doi.org\/10.1016\/j.automatica.2018.03.046","journal-title":"Automatica"},{"key":"4_CR33","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"265","DOI":"10.1007\/978-3-030-57628-8_16","volume-title":"Formal Modeling and Analysis of Timed Systems","author":"D Li","year":"2020","unstructured":"Li, D., Bak, S., Bogomolov, S.: Reachability analysis of nonlinear systems using hybridization and dynamics scaling. In: Bertrand, N., Jansen, N. (eds.) FORMATS 2020. LNCS, vol. 12288, pp. 265\u2013282. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-57628-8_16"},{"key":"4_CR34","doi-asserted-by":"crossref","unstructured":"Luo, J.H., Wu, J., Lin, W.: Thinet: a filter level pruning method for deep neural network compression. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 5058\u20135066 (2017)","DOI":"10.1109\/ICCV.2017.541"},{"issue":"1","key":"4_CR35","doi-asserted-by":"publisher","first-page":"4950","DOI":"10.1038\/s41467-018-07210-0","volume":"9","author":"B Lusch","year":"2018","unstructured":"Lusch, B., Kutz, J.N., Brunton, S.L.: Deep learning for universal linear embeddings of nonlinear dynamics. Nat. Commun. 9(1), 4950 (2018). https:\/\/doi.org\/10.1038\/s41467-018-07210-0","journal-title":"Nat. Commun."},{"key":"4_CR36","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"362","DOI":"10.1007\/978-3-642-31424-7_28","volume-title":"Computer Aided Verification","author":"R Majumdar","year":"2012","unstructured":"Majumdar, R., Zamani, M.: Approximately bisimilar symbolic models for digital control systems. In: Madhusudan, P., Seshia, S.A. (eds.) CAV 2012. LNCS, vol. 7358, pp. 362\u2013377. Springer, Heidelberg (2012). https:\/\/doi.org\/10.1007\/978-3-642-31424-7_28"},{"key":"4_CR37","unstructured":"Martin, C.H., Mahoney, M.W.: Implicit self-regularization in deep neural networks: evidence from random matrix theory and implications for learning. J. Mach. Learn. Res. 22(1) (2021)"},{"key":"4_CR38","unstructured":"Memmel, E., Menzen, C., Schuurmans, J., Wesel, F., Batselier, K.: Position: tensor networks are a valuable asset for green AI. In: Proceedings of the 41st International Conference on Machine Learning. Proceedings of Machine Learning Research, vol.\u00a0235, pp. 35340\u201335353. PMLR (2024)"},{"key":"4_CR39","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1016\/j.disopt.2016.01.005","volume":"19","author":"DR Morrison","year":"2016","unstructured":"Morrison, D.R., Jacobson, S.H., Sauppe, J.J.: Branch-and-bound algorithms: a survey of recent advances in searching, branching, and pruning. Disc. Optim. 19, 79\u2013102 (2016). https:\/\/doi.org\/10.1016\/j.disopt.2016.01.005","journal-title":"Disc. Optim."},{"issue":"12","key":"4_CR40","doi-asserted-by":"publisher","first-page":"3210","DOI":"10.1109\/TAC.2015.2422431","volume":"60","author":"P Prabhakar","year":"2015","unstructured":"Prabhakar, P., Dullerud, G.E., Viswanathan, M.: Stability preserving simulations and bisimulations for hybrid systems. IEEE Trans. Autom. Control 60(12), 3210\u20133225 (2015)","journal-title":"IEEE Trans. Autom. Control"},{"key":"4_CR41","volume-title":"Model Predictive Control: Theory, Computation, and Design","author":"JB Rawlings","year":"2017","unstructured":"Rawlings, J.B., Mayne, D.Q., Diehl, M.M.: Model Predictive Control: Theory, Computation, and Design, 2nd edn. Nob Hill Publishing, Madison (2017)","edition":"2"},{"key":"4_CR42","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"752","DOI":"10.1007\/978-3-662-49674-9_48","volume-title":"Tools and Algorithms for the Construction and Analysis of Systems","author":"N Roohi","year":"2016","unstructured":"Roohi, N., Prabhakar, P., Viswanathan, M.: Hybridization based CEGAR for hybrid automata with affine dynamics. In: Chechik, M., Raskin, J.-F. (eds.) TACAS 2016. LNCS, vol. 9636, pp. 752\u2013769. Springer, Heidelberg (2016). https:\/\/doi.org\/10.1007\/978-3-662-49674-9_48"},{"key":"4_CR43","volume-title":"Nonlinear Systems, Interdisciplinary Applied Mathematics","author":"S Sastry","year":"1999","unstructured":"Sastry, S.: Nonlinear Systems, Interdisciplinary Applied Mathematics, vol. 10. Springer, New York (1999)"},{"key":"4_CR44","doi-asserted-by":"crossref","unstructured":"Solanki, P., Vertovec, N., Schnitzer, Y., Beers, J.V., de\u00a0Visser, C., Abate, A.: Certified approximate reachability (care): formal error bounds on deep learning of reachable sets. arXiv preprint arXiv:2503.23912 (2025)","DOI":"10.1109\/CDC57313.2025.11312709"},{"key":"4_CR45","doi-asserted-by":"publisher","unstructured":"Solar-Lezama, A., Tancau, L., Bodik, R., Seshia, S., Saraswat, V.: Combinatorial sketching for finite programs. In: Proceedings of the 12th International Conference on Architectural Support for Programming Languages and Operating Systems, ASPLOS XII, pp. 404\u2013415. Association for Computing Machinery (2006). https:\/\/doi.org\/10.1145\/1168857.1168907","DOI":"10.1145\/1168857.1168907"},{"key":"4_CR46","unstructured":"Villani, M.J., Schoots, N.: Any deep relu network is shallow. arXiv preprint arXiv:2306.11827 (2023)"},{"key":"4_CR47","doi-asserted-by":"publisher","unstructured":"Wu, H., et al.: Marabou 2.0: A Versatile Formal Analyzer of Neural Networks, pp. 249\u2013264. Springer, Cham (2024). https:\/\/doi.org\/10.1007\/978-3-031-65630-9_13","DOI":"10.1007\/978-3-031-65630-9_13"},{"key":"4_CR48","first-page":"1129","volume":"33","author":"K Xu","year":"2020","unstructured":"Xu, K., et al.: Automatic perturbation analysis for scalable certified robustness and beyond. Adv. Neural. Inf. Process. Syst. 33, 1129\u20131141 (2020)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"4_CR49","doi-asserted-by":"publisher","first-page":"1656","DOI":"10.52202\/068431-0121","volume":"35","author":"H Zhang","year":"2022","unstructured":"Zhang, H., et al.: General cutting planes for bound-propagation-based neural network verification. Adv. Neural. Inf. Process. Syst. 35, 1656\u20131670 (2022)","journal-title":"Adv. Neural. Inf. Process. Syst."}],"container-title":["Lecture Notes in Computer Science","AI Verification"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-32357-6_4","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,17]],"date-time":"2026-07-17T10:36:33Z","timestamp":1784284593000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-32357-6_4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,18]]},"ISBN":["9783032323569","9783032323576"],"references-count":49,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-32357-6_4","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,18]]},"assertion":[{"value":"18 July 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"SAIV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Symposium on AI Verification","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Lisbon","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Portugal","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2026","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24 July 2026","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25 July 2026","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"saiv2026","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/aiverification.org\/2026","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}