{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,5]],"date-time":"2025-07-05T11:10:11Z","timestamp":1751713811111,"version":"3.41.0"},"publisher-location":"Cham","reference-count":22,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031976476"},{"type":"electronic","value":"9783031976483"}],"license":[{"start":{"date-parts":[[2025,6,28]],"date-time":"2025-06-28T00:00:00Z","timestamp":1751068800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,6,28]],"date-time":"2025-06-28T00:00:00Z","timestamp":1751068800000},"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":[[2026]]},"DOI":"10.1007\/978-3-031-97648-3_19","type":"book-chapter","created":{"date-parts":[[2025,7,5]],"date-time":"2025-07-05T10:29:16Z","timestamp":1751711356000},"page":"282-293","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Neural Ordinary Differential Equations with\u00a0TM-Solver to\u00a0Predict Time Series Data"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8906-5227","authenticated-orcid":false,"given":"Anna","family":"Golovkina","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0002-9532-6312","authenticated-orcid":false,"given":"Anna","family":"Vashukova","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,6,28]]},"reference":[{"key":"19_CR1","unstructured":"Delhi Weather Data. https:\/\/www.kaggle.com\/datasets\/mahirkukreja\/delhi-weather-data"},{"key":"19_CR2","doi-asserted-by":"publisher","unstructured":"Solving Ordinary Differential Equations I, Springer Series in Computational Mathematics, vol.\u00a08. Springer Berlin Heidelberg, Berlin, Heidelberg (1993). https:\/\/doi.org\/10.1007\/978-3-540-78862-1","DOI":"10.1007\/978-3-540-78862-1"},{"key":"19_CR3","doi-asserted-by":"crossref","unstructured":"Atkinson, K., Han, W., Stewart, D.E.: Numerical Solution of Ordinary Differential Equations. John Wiley & Sons (2009)","DOI":"10.1002\/9781118164495"},{"key":"19_CR4","doi-asserted-by":"publisher","unstructured":"Bilo\u0161, M., Sommer, J., Rangapuram, S.S., Januschowski, T., G\u00fcnnemann, S.: Neural Flows: Efficient Alternative to Neural ODEs (2021). https:\/\/doi.org\/10.48550\/arXiv.2110.13040, http:\/\/arxiv.org\/abs\/2110.13040, arXiv:2110.13040 [cs]","DOI":"10.48550\/arXiv.2110.13040"},{"key":"19_CR5","doi-asserted-by":"publisher","unstructured":"Botev, A., Jaegle, A., Wirnsberger, P., Hennes, D., Higgins, I.: Which priors matter? Benchmarking models for learning latent dynamics (2021). https:\/\/doi.org\/10.48550\/arXiv.2111.05458, http:\/\/arxiv.org\/abs\/2111.05458, arXiv:2111.05458 [stat]","DOI":"10.48550\/arXiv.2111.05458"},{"key":"19_CR6","doi-asserted-by":"publisher","unstructured":"Chen, R.T.Q., Rubanova, Y., Bettencourt, J., Duvenaud, D.: Neural Ordinary Differential Equations (2019). https:\/\/doi.org\/10.48550\/arXiv.1806.07366, http:\/\/arxiv.org\/abs\/1806.07366, arXiv:1806.07366 [cs]","DOI":"10.48550\/arXiv.1806.07366"},{"key":"19_CR7","unstructured":"Dupont, E., Doucet, A., Teh, Y.W.: Augmented Neural ODEs. In: Advances in Neural Information Processing Systems. vol.\u00a032. Curran Associates, Inc. (2019)"},{"key":"19_CR8","doi-asserted-by":"publisher","unstructured":"Fronk, C., Petzold, L.: Interpretable polynomial neural ordinary differential equations. Chaos 33(4) (2023). https:\/\/doi.org\/10.1063\/5.0130803, https:\/\/www.ncbi.nlm.nih.gov\/pmc\/articles\/PMC10076068\/","DOI":"10.1063\/5.0130803"},{"key":"19_CR9","doi-asserted-by":"publisher","unstructured":"Gholami, A., Keutzer, K., Biros, G.: ANODE: Unconditionally Accurate Memory-Efficient Gradients for Neural ODEs (2019). https:\/\/doi.org\/10.48550\/arXiv.1902.10298, http:\/\/arxiv.org\/abs\/1902.10298, arXiv:1902.10298 [cs]","DOI":"10.48550\/arXiv.1902.10298"},{"key":"19_CR10","doi-asserted-by":"crossref","unstructured":"Golovkina, A., Kozynchenko, V.: Neural network representation for ordinary differential equations. In: Artificial Intelligence in Models, Methods and Applications, Studies in Systems, Decision and Control, vol.\u00a0457. Springer International Publishing (2022)","DOI":"10.1007\/978-3-031-22938-1_3"},{"key":"19_CR11","doi-asserted-by":"publisher","unstructured":"Golovkina, A., Kozynchenko, V., Kulabukhova, N.: Reconstruction and identification of dynamical systems based on Taylor maps. In: Gervasi, O., et al. (eds.) Computational Science and Its Applications \u2013 ICCSA 2021, vol. 12956, pp. 360\u2013369. Springer International Publishing, Cham (2021).https:\/\/doi.org\/10.1007\/978-3-030-87010-2_26, https:\/\/link.springer.com\/10.1007\/978-3-030-87010-2_26, series Title: Lecture Notes in Computer Science","DOI":"10.1007\/978-3-030-87010-2_26"},{"key":"19_CR12","doi-asserted-by":"publisher","unstructured":"Greydanus, S., Dzamba, M., Yosinski, J.: Hamiltonian Neural Networks (2019). https:\/\/doi.org\/10.48550\/arXiv.1906.01563, arXiv:1906.01563 [cs]","DOI":"10.48550\/arXiv.1906.01563"},{"key":"19_CR13","doi-asserted-by":"publisher","unstructured":"Huang, Z., Sun, Y., Wang, W.: Learning Continuous System Dynamics from Irregularly-Sampled Partial Observations (2020). https:\/\/doi.org\/10.48550\/arXiv.2011.03880","DOI":"10.48550\/arXiv.2011.03880"},{"key":"19_CR14","doi-asserted-by":"publisher","unstructured":"Kidger, P.: On Neural Differential Equations (2022). https:\/\/doi.org\/10.48550\/arXiv.2202.02435, http:\/\/arxiv.org\/abs\/2202.02435","DOI":"10.48550\/arXiv.2202.02435"},{"key":"19_CR15","doi-asserted-by":"publisher","unstructured":"Kidger, P., Morrill, J., Foster, J., Lyons, T.: Neural Controlled Differential Equations for Irregular Time Series (2020). https:\/\/doi.org\/10.48550\/arXiv.2005.08926, http:\/\/arxiv.org\/abs\/2005.08926, arXiv:2005.08926 [cs]","DOI":"10.48550\/arXiv.2005.08926"},{"key":"19_CR16","doi-asserted-by":"publisher","unstructured":"Klimenko, I., Golovkina, A., Ruzhnikov, V.: Polynomial neural layers for numerical modeling of dynamical processes. In: Gervasi, O., Murgante, B., Rocha, A.M.A.C., Garau, C., Scorza, F., Karaca, Y., Torre, C.M. (eds.) Computational Science and Its Applications \u2013 ICCSA 2023 Workshops, vol. 14109, pp. 261\u2013273. Springer Nature Switzerland, Cham (2023https:\/\/doi.org\/10.1007\/978-3-031-37120-2_17, https:\/\/link.springer.com\/10.1007\/978-3-031-37120-2_17, series Title: Lecture Notes in Computer Science","DOI":"10.1007\/978-3-031-37120-2_17"},{"key":"19_CR17","doi-asserted-by":"publisher","unstructured":"Lechner, M., Hasani, R.: Learning Long-Term Dependencies in Irregularly-Sampled Time Series (2020). https:\/\/doi.org\/10.48550\/arXiv.2006.04418, http:\/\/arxiv.org\/abs\/2006.04418, arXiv:2006.04418 [cs]","DOI":"10.48550\/arXiv.2006.04418"},{"key":"19_CR18","doi-asserted-by":"publisher","unstructured":"Margasov, A.: Neural ordinary differential equations and their probabilistic extension. In: Proceedings of the Komi Science Centre of the Ural Division of the Russian Academy of Sciences, vol. 6, pp. 14\u201319 (2021). https:\/\/doi.org\/10.19110\/1994-5655-2021-6-14-19, https:\/\/www.elibrary.ru\/item.asp?id=47501514","DOI":"10.19110\/1994-5655-2021-6-14-19"},{"key":"19_CR19","doi-asserted-by":"publisher","unstructured":"Pal, A., Ma, Y., Shah, V., Rackauckas, C.: Opening the Blackbox: Accelerating Neural Differential Equations by Regularizing Internal Solver Heuristics (2022). https:\/\/doi.org\/10.48550\/arXiv.2105.03918, http:\/\/arxiv.org\/abs\/2105.03918, arXiv:2105.03918 [cs]","DOI":"10.48550\/arXiv.2105.03918"},{"key":"19_CR20","doi-asserted-by":"publisher","unstructured":"Poli, M., Massaroli, S., Yamashita, A., Asama, H., Park, J.: Hypersolvers: Toward Fast Continuous-Depth Models (2020). https:\/\/doi.org\/10.48550\/arXiv.2007.09601, http:\/\/arxiv.org\/abs\/2007.09601","DOI":"10.48550\/arXiv.2007.09601"},{"key":"19_CR21","doi-asserted-by":"publisher","unstructured":"Pontryagin, L.: Mathematical Theory of Optimal Processes. Routledge, 1 edn. (2018). https:\/\/doi.org\/10.1201\/9780203749319, https:\/\/www.taylorfrancis.com\/books\/9780203749319","DOI":"10.1201\/9780203749319"},{"key":"19_CR22","doi-asserted-by":"publisher","unstructured":"Zhu, A., Jin, P., Zhu, B., Tang, Y.: On Numerical Integration in Neural Ordinary Differential Equations (2022). https:\/\/doi.org\/10.48550\/arXiv.2206.07335, http:\/\/arxiv.org\/abs\/2206.07335, arXiv:2206.07335 [cs]","DOI":"10.48550\/arXiv.2206.07335"}],"container-title":["Lecture Notes in Computer Science","Computational Science and Its Applications \u2013 ICCSA 2025 Workshops"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-97648-3_19","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,5]],"date-time":"2025-07-05T10:29:21Z","timestamp":1751711361000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-97648-3_19"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,28]]},"ISBN":["9783031976476","9783031976483"],"references-count":22,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-97648-3_19","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2025,6,28]]},"assertion":[{"value":"28 June 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICCSA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Computational Science and Its Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Istanbul","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"T\u00fcrkiye","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"30 June 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3 July 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iccsa2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/iccsa.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}