Convolutional embedding of attributed molecular graphs for physical property prediction
Coley, Connor W., Barzilay, Regina, Green, William H., Jaakkola, Tommi S., Jensen, Klavs F.·2017·Journal of Chemical Information and Modeling
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- TutorialCao Xiao, Jimeng Sun · 2019 · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)
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