1 code implementation • ICML 2020 • Sai Krishna Gottipati, Boris Sattarov, Sufeng. Niu, Hao-Ran Wei, Yashaswi Pathak, Shengchao Liu, Simon Blackburn, Karam Thomas, Connor Coley, Jian Tang, Sarath Chandar, Yoshua Bengio
In this work, we propose a novel reinforcement learning (RL) setup for drug discovery that addresses this challenge by embedding the concept of synthetic accessibility directly into the de novo compound design system.
1 code implementation • 26 Apr 2020 • Sai Krishna Gottipati, Boris Sattarov, Sufeng. Niu, Yashaswi Pathak, Hao-Ran Wei, Shengchao Liu, Karam M. J. Thomas, Simon Blackburn, Connor W. Coley, Jian Tang, Sarath Chandar, Yoshua Bengio
Over the last decade, there has been significant progress in the field of machine learning for de novo drug design, particularly in deep generative models.
no code implementations • 26 Jun 2019 • Siheng Chen, Sufeng. Niu, Tian Lan, Baoan Liu
We present a novel graph-neural-network-based system to effectively represent large-scale 3D point clouds with the applications to autonomous driving.
1 code implementation • 8 Jun 2017 • Sufeng. Niu, Siheng Chen, Hanyu Guo, Colin Targonski, Melissa C. Smith, Jelena Kovačević
GVIN emulates the value iteration algorithm by using a novel graph convolution operator, which enables GVIN to learn and plan on irregular spatial graphs.