Self-supervised learning method for molecular dynamics simulation using graph neural network to obtain molecular geometry features

Satoki Ishiai

[PS1-36] Self-supervised learning method for molecular dynamics simulation using graph neural network to obtain molecular geometry features

*Satoki Ishiai¹, Katsuhiro Endo^1,2, Kenji Yasuoka¹ (1. Keio University (Japan), 2. National Institute of Advanced Industrial Science and Technology (AIST) (Japan))

キーワード：machine learning, graph neural network, unsupervised learning, contrastive learning

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Poster 1

[PS1-36] Self-supervised learning method for molecular dynamics simulation using graph neural network to obtain molecular geometry features

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