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cs.LG2019★ 170 cited
SMILES Transformer: Pre-trained Molecular Fingerprint for Low Data Drug Discovery
Shion Honda, Shoi Shi, Hiroki R. Ueda
In drug-discovery-related tasks such as virtual screening, machine learning is emerging as a promising way to predict molecular properties. Conventionally, molecular fingerprints (…
cs.LG2019★ 31 cited
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…