1 code implementation • 17 Aug 2022 • Duo Zhang, Hangrui Bi, Fu-Zhi Dai, Wanrun Jiang, Linfeng Zhang, Han Wang
Machine learning assisted modeling of the inter-atomic potential energy surface (PES) is revolutionizing the field of molecular simulation.
no code implementations • 29 Sep 2021 • Yuchen Liu, Yali Du, Runji Lin, Hangrui Bi, Mingdong Wu, Jun Wang, Hao Dong
Model-based RL is an effective approach for reducing sample complexity.
Model-based Reinforcement Learning Reinforcement Learning (RL)
no code implementations • 8 Jun 2021 • Hangrui Bi, Hengyi Wang, Chence Shi, Connor Coley, Jian Tang, Hongyu Guo
Reliably predicting the products of chemical reactions presents a fundamental challenge in synthetic chemistry.
no code implementations • 16 Dec 2020 • Hangrui Bi, Hengyi Wang, Chence Shi, Jian Tang
Our model achieves both an order of magnitude lower inference latency, with state-of-the-art top-1 accuracy and comparable performance on Top-K sampling.