Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation

NeurIPS 2018 Jiaxuan YouBowen LiuRex YingVijay PandeJure Leskovec

Generating novel graph structures that optimize given objectives while obeying some given underlying rules is fundamental for chemistry, biology and social science research. This is especially important in the task of molecular graph generation, whose goal is to discover novel molecules with desired properties such as drug-likeness and synthetic accessibility, while obeying physical laws such as chemical valency... (read more)

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