31 citations · 35 across the 2 of their papers we have counts for
4 papers
Data Transfer Approaches to Improve Seq-to-Seq Retrosynthesis
Katsuhiko Ishiguro, Kazuya Ujihara, Ryohto Sawada +2
Retrosynthesis is a problem to infer reactant compounds to synthesize a given product compound through chemical reactions. Recent studies on retrosynthesis focus on proposing more…
Graph Residual Flow for Molecular Graph Generation
Shion Honda, Hirotaka Akita, Katsuhiko Ishiguro +2
Statistical generative models for molecular graphs attract attention from many researchers from the fields of bio- and chemo-informatics. Among these models, invertible flow-based…
Dual Convolutional Neural Network for Graph of Graphs Link Prediction
Shonosuke Harada, Hirotaka Akita, Masashi Tsubaki +4
Graphs are general and powerful data representations which can model complex real-world phenomena, ranging from chemical compounds to social networks; however, effective feature ex…
BayesGrad: Explaining Predictions of Graph Convolutional Networks
Hirotaka Akita, Kosuke Nakago, Tomoki Komatsu +4
Recent advances in graph convolutional networks have significantly improved the performance of chemical predictions, raising a new research question: "how do we explain the predict…