{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,13]],"date-time":"2026-01-13T14:10:44Z","timestamp":1768313444208,"version":"3.49.0"},"reference-count":24,"publisher":"IEEE","license":[{"start":{"date-parts":[[2025,11,25]],"date-time":"2025-11-25T00:00:00Z","timestamp":1764028800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,11,25]],"date-time":"2025-11-25T00:00:00Z","timestamp":1764028800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,11,25]]},"DOI":"10.1109\/candarw68385.2025.00026","type":"proceedings-article","created":{"date-parts":[[2026,1,12]],"date-time":"2026-01-12T18:20:34Z","timestamp":1768242034000},"page":"109-112","source":"Crossref","is-referenced-by-count":0,"title":["On implicit gradient regularization in neural-ordinary-differential-equation control"],"prefix":"10.1109","author":[{"given":"A.Y.","family":"Vasilyev","sequence":"first","affiliation":[{"name":"Beijing Normal University Hong Kong Baptist University,Zhuhai,China"}]}],"member":"263","reference":[{"issue":"165","key":"ref1","first-page":"1","article-title":"Implicit self-regularization in deep neural networks: Evidence from random matrix theory and implications for learning","volume":"22","author":"Martin","year":"2021","journal-title":"Journal of Machine Learning Research"},{"key":"ref2","article-title":"Implicit gradient regularization","author":"Barrett","year":"2022"},{"key":"ref3","article-title":"In search of the real inductive bias: On the role of implicit regularization in deep learning","author":"Neyshabur","year":"2015"},{"key":"ref4","article-title":"An empirical study of implicit regularization in deep offline rl","author":"Gulcehre","year":"2022"},{"key":"ref5","first-page":"5862","article-title":"On the implicit bias of Adam","volume-title":"Proceedings of the 41st International Conference on Machine Learning, ser. Proceedings of Machine Learning Research","volume":"235","author":"Cattaneo"},{"key":"ref6","doi-asserted-by":"crossref","DOI":"10.1137\/18M1203997","article-title":"Multiscale analysis of accelerated gradient methods","author":"Farazmand","year":"2020"},{"key":"ref7","article-title":"Adam: A method for stochastic optimization","author":"Kingma","year":"2017"},{"key":"ref8","article-title":"Neural ordinary differential equations","volume":"31","author":"Chen","year":"2018","journal-title":"Advances in neural information processing systems"},{"key":"ref9","article-title":"Neural ordinary differential equations for intervention modeling","author":"Gwak","year":"2020"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcp.2022.111838"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1090\/gsm\/252\/23"},{"key":"ref12","article-title":"Learning differential equations that are easy to solve","author":"Kelly","year":"2020"},{"key":"ref13","article-title":"Symplectic ode-net: Learning hamiltonian dynamics with control","author":"Zhong"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-021-27590-0"},{"key":"ref15","article-title":"Implicit energy regularization of neural ordinary-differential-equation control","author":"B\u00e9ttcher","year":"2021","journal-title":"arXiv preprint arXiv:2103.06525"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1088\/2632-2153\/ac92c3"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevResearch.4.013221"},{"key":"ref18","article-title":"Efficient and accurate gradients for neural sdes","author":"Kidger","year":"2021"},{"key":"ref19","article-title":"The DeepMind JAX Ecosystem","year":"2020"},{"key":"ref20","article-title":"Gram-gauss-newton method: Learning overparameterized neural networks for regression problems","author":"Cai","year":"2019"},{"key":"ref21","article-title":"Rethinking gauss-newton for learning overparameterized models","author":"Arbel","year":"2023"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevLett.108.218703"},{"key":"ref23","doi-asserted-by":"crossref","DOI":"10.3389\/fenrg.2020.00115","article-title":"A stochastic approach to the synchronization of coupled oscillators","author":"Biccari","year":"2020"},{"key":"ref24","article-title":"On the stability of the kuramoto model of coupled nonlinear oscillators","author":"Jadbabaie","year":"2005"}],"event":{"name":"2025 Thirteenth International Symposium on Computing and Networking Workshops (CANDARW)","location":"Yamagata, Japan","start":{"date-parts":[[2025,11,25]]},"end":{"date-parts":[[2025,11,28]]}},"container-title":["2025 Thirteenth International Symposium on Computing and Networking Workshops (CANDARW)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11318850\/11318884\/11318916.pdf?arnumber=11318916","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,13]],"date-time":"2026-01-13T08:36:54Z","timestamp":1768293414000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11318916\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,25]]},"references-count":24,"URL":"https:\/\/doi.org\/10.1109\/candarw68385.2025.00026","relation":{},"subject":[],"published":{"date-parts":[[2025,11,25]]}}}