The Symplectic Adjoint Method: Memory-Efficient Backpropagation of Neural-Network-Based Differential Equations
Author:
Affiliation:
1. Graduate School of Engineering Science, Osaka University, Osaka, Japan
2. Cybermedia Center, Osaka University, Osaka, Japan
3. Graduate School of System Informatics, Kobe University, Hyogo, Japan
Funder
Japan Science and Technology Agency (JST) Core Research for Evolutionary Science and Technology
JST Precursory Research for Embryonic Science and Technology
Japan Society for the Promotion of Science (JSPS) Grants-in-Aid for Scientific Research
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Artificial Intelligence,Computer Networks and Communications,Computer Science Applications,Software
Link
http://xplorestaging.ieee.org/ielx7/5962385/6104215/10045756.pdf?arnumber=10045756
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