Presentation | 2021-06-28 Training Neural ODE by Symplectic Integrator Takashi Matsubara, Yuto Miyatake, Takaharu Yaguchi, |
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PDF Download Page | PDF download Page Link |
Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | A differential equation model using neural networks, neural ODE, enables use to model a continuous-time dynamics and probabilistic model with high accuracy. However, the neural ODE uses the same neural network repeatedly, the training using the backpropagation algorithm consumes large memory. Instead of the backpropagation algorithm, the adjoint method is commonly used, which obtains the gradient using the numerical integration. The adjoint method needs a small step size and much computational cost to suppress the numerical errors. In this study, we combine the checkpointing scheme and symplectic integrator for the adjoint method. It suppresses the memory consumption and functions faster. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Neural ODE / ordinary differential equation / adjoint method / symplectic integrator |
Paper # | NC2021-2,IBISML2021-2 |
Date of Issue | 2021-06-21 (NC, IBISML) |
Conference Information | |
Committee | NC / IBISML / IPSJ-BIO / IPSJ-MPS |
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Conference Date | 2021/6/28(3days) |
Place (in Japanese) | (See Japanese page) |
Place (in English) | Online |
Topics (in Japanese) | (See Japanese page) |
Topics (in English) | |
Chair | Rieko Osu(Waseda Univ.) / Ichiro Takeuchi(Nagoya Inst. of Tech.) / 倉田 博之(九工大) / 関嶋 政和(東工大) |
Vice Chair | Hiroshi Yamakawa(Univ of Tokyo) / Masashi Sugiyama(Univ. of Tokyo) |
Secretary | Hiroshi Yamakawa(ATR) / Masashi Sugiyama(NICT) / (Univ. of Tokyo) / (AIST) |
Assistant | Nobuhiko Wagatsuma(Toho Univ.) / Tomoki Kurikawa(KMU) / Tomoharu Iwata(NTT) / Atsuyoshi Nakamura(Hokkaido Univ.) |
Paper Information | |
Registration To | Technical Committee on Neurocomputing / Technical Committee on Infomation-Based Induction Sciences and Machine Learning / Special Interest Group on Bioinformatics and Genomics / Special Interest Group on Mathematical Modeling and Problem Solving |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Training Neural ODE by Symplectic Integrator |
Sub Title (in English) | |
Keyword(1) | Neural ODE |
Keyword(2) | ordinary differential equation |
Keyword(3) | adjoint method |
Keyword(4) | symplectic integrator |
1st Author's Name | Takashi Matsubara |
1st Author's Affiliation | Osaka University(Osaka Univ.) |
2nd Author's Name | Yuto Miyatake |
2nd Author's Affiliation | Osaka University(Osaka Univ.) |
3rd Author's Name | Takaharu Yaguchi |
3rd Author's Affiliation | Kobe University(Kobe Univ.) |
Date | 2021-06-28 |
Paper # | NC2021-2,IBISML2021-2 |
Volume (vol) | vol.121 |
Number (no) | NC-79,IBISML-80 |
Page | pp.pp.9-14(NC), pp.9-14(IBISML), |
#Pages | 6 |
Date of Issue | 2021-06-21 (NC, IBISML) |