{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T04:13:39Z","timestamp":1783052019112,"version":"3.54.6"},"reference-count":34,"publisher":"IEEE","license":[{"start":{"date-parts":[[2023,2,1]],"date-time":"2023-02-01T00:00:00Z","timestamp":1675209600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,2,1]],"date-time":"2023-02-01T00:00:00Z","timestamp":1675209600000},"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":[[2023,2]]},"DOI":"10.1109\/hpca56546.2023.10070935","type":"proceedings-article","created":{"date-parts":[[2023,3,24]],"date-time":"2023-03-24T17:42:55Z","timestamp":1679679775000},"page":"802-813","source":"Crossref","is-referenced-by-count":4,"title":["eNODE: Energy-Efficient and Low-Latency Edge Inference and Training of Neural ODEs"],"prefix":"10.1109","author":[{"given":"Junkang","family":"Zhu","sequence":"first","affiliation":[{"name":"University of Michigan, Ann Arbor,Ann Arbor,Michigan,USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yaoyu","family":"Tao","sequence":"additional","affiliation":[{"name":"University of Michigan, Ann Arbor,Ann Arbor,Michigan,USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhengya","family":"Zhang","sequence":"additional","affiliation":[{"name":"University of Michigan, Ann Arbor,Ann Arbor,Michigan,USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/MICRO.2016.7783725"},{"key":"ref2","first-page":"342","article-title":"The shattered gradients problem: If resnets are the answer, then what is the question?","volume-title":"International Conference on Machine Learning","author":"Balduzzi"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1090\/hmath\/011"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11668"},{"key":"ref5","article-title":"Neural ordinary differential equations","volume-title":"Advances in Neural Information Processing Systems","volume":"31","author":"Chen","year":"2018"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2012.2211477"},{"key":"ref7","article-title":"Augmented neural odes","volume-title":"Advances in Neural Information Processing Systems","volume":"32","author":"Dupont","year":"2019"},{"key":"ref8","volume-title":"Low-order classical Runge-Kutta formulas with stepsize control and their application to some heat transfer problems","volume":"315","author":"Fehlberg","year":"1969"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/103"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/JETCAS.2019.2905361"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.23919\/VLSICircuits52068.2021.9492338"},{"key":"ref12","article-title":"Identity matters in deep learning","volume-title":"International Conference on Learning Representations","author":"Hardt"},{"issue":"9","key":"ref13","first-page":"7657","article-title":"Liquid time-constant networks","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence","volume":"35","author":"Hasani"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46493-0_38"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.243"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/LCA.2015.2414456"},{"issue":"1","key":"ref18","first-page":"1","article-title":"Cifar-10 and cifar-100 datasets","volume":"6","author":"Krizhevsky","year":"2009"},{"key":"ref19","article-title":"Visualizing the loss landscape of neural nets","volume-title":"Advances in Neural Information Processing Systems","volume":"31","author":"Li","year":"2018"},{"key":"ref20","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-319-70139-4","article-title":"Convergence analysis of two-layer neural networks with relu activation","volume-title":"Advances in Neural Information Processing Systems","volume":"30","author":"Li","year":"2017"},{"key":"ref21","first-page":"3952","article-title":"Dissecting neural odes","volume-title":"Advances in Neural Information Processing Systems","volume":"33","author":"Massaroli","year":"2020"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ISSCC.2017.7870353"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1063\/1.4823060"},{"key":"ref24","article-title":"Continuous-in-depth neural networks","author":"Queiruga","year":"2020","journal-title":"arXiv preprint arXiv:2008.02389"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1007\/BF01446807"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00474"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1145\/3466752.3480052"},{"key":"ref28","article-title":"Residual networks behave like ensembles of relatively shallow networks","volume-title":"Advances in Neural Information Processing Systems","volume":"29","author":"Veit","year":"2016"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1093\/icesjms\/3.1.3"},{"key":"ref30","article-title":"On robustness of neural ordinary differential equations","volume-title":"International Conference on Learning Representations","author":"Yan"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.5244\/C.30.87"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.415"},{"key":"ref33","first-page":"11 639","article-title":"Adaptive checkpoint adjoint method for gradient estimation in neural ode","volume-title":"International Conference on Machine Learning","author":"Zhuang"},{"key":"ref34","article-title":"Mali: A memory efficient and reverse accurate integrator for neural odes","volume-title":"International Conference on Learning Representations","author":"Zhuang"}],"event":{"name":"2023 IEEE International Symposium on High-Performance Computer Architecture (HPCA)","location":"Montreal, QC, Canada","start":{"date-parts":[[2023,2,25]]},"end":{"date-parts":[[2023,3,1]]}},"container-title":["2023 IEEE International Symposium on High-Performance Computer Architecture (HPCA)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10070856\/10070923\/10070935.pdf?arnumber=10070935","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,2,13]],"date-time":"2024-02-13T13:12:38Z","timestamp":1707829958000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10070935\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,2]]},"references-count":34,"URL":"https:\/\/doi.org\/10.1109\/hpca56546.2023.10070935","relation":{},"subject":[],"published":{"date-parts":[[2023,2]]}}}