AutoInt: Automatic Feature Interaction Learning via Self-Attentive Neural Networks. - Weiping Song; Chence Shi; Zhiping Xiao 001; Zhijian Duan 001; Yewen Xu; Ming Zhang 004; Jian Tang 005 (CIKM, 2019)

GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation. - Chence Shi; Minkai Xu; Zhaocheng Zhu; Weinan Zhang 001; Ming Zhang 004; Jian Tang 005 (ICLR, 2020)

A Graph to Graphs Framework for Retrosynthesis Prediction. - Chence Shi; Minkai Xu; Hongyu Guo; Ming Zhang 004; Jian Tang 005 (ICML, 2020)

MARS: Markov Molecular Sampling for Multi-objective Drug Discovery. - Yutong Xie 007; Chence Shi; Hao Zhou 012; Yuwei Yang; Weinan Zhang 001; Yong Yu 001; Lei Li 005 (ICLR, 2021)

Non-Autoregressive Electron Redistribution Modeling for Reaction Prediction. - Hangrui Bi; Hengyi Wang; Chence Shi; Connor W. Coley; Jian Tang 005; Hongyu Guo (ICML, 2021)

Learning Gradient Fields for Molecular Conformation Generation. - Chence Shi; Shitong Luo; Minkai Xu; Jian Tang 005 (ICML, 2021)

An End-to-End Framework for Molecular Conformation Generation via Bilevel Programming. - Minkai Xu; Wujie Wang; Shitong Luo; Chence Shi; Yoshua Bengio; Rafael Gómez-Bombarelli; Jian Tang 005 (ICML, 2021)

Predicting Molecular Conformation via Dynamic Graph Score Matching. - Shitong Luo; Chence Shi; Minkai Xu; Jian Tang 005 (NeurIPS, 2021)

GeoDiff: A Geometric Diffusion Model for Molecular Conformation Generation. - Minkai Xu; Lantao Yu; Yang Song 011; Chence Shi; Stefano Ermon; Jian Tang 005 (ICLR, 2022)

TorchDrug: A Powerful and Flexible Machine Learning Platform for Drug Discovery. - Zhaocheng Zhu; Chence Shi; Zuobai Zhang; Shengchao Liu; Minghao Xu; Xinyu Yuan; Yangtian Zhang; Jun-Kun Chen; Huiyu Cai; Jiarui Lu; Chang Ma; Runcheng Liu; et al. (CoRR, 2022)

E3Bind: An End-to-End Equivariant Network for Protein-Ligand Docking. - Yangtian Zhang; Huiyu Cai; Chence Shi; Bozitao Zhong; Jian Tang 005 (CoRR, 2022)

Protein Sequence and Structure Co-Design with Equivariant Translation. - Chence Shi; Chuanrui Wang; Jiarui Lu; Bozitao Zhong; Jian Tang 005 (ICLR, 2023)

E3Bind: An End-to-End Equivariant Network for Protein-Ligand Docking. - Yangtian Zhang; Huiyu Cai; Chence Shi; Jian Tang 005 (ICLR, 2023)

Fusing Neural and Physical: Augment Protein Conformation Sampling with Tractable Simulations. - Jiarui Lu; Zuobai Zhang; Bozitao Zhong; Chence Shi; Jian Tang 005 (CoRR, 2024)

Structure Language Models for Protein Conformation Generation. - Jiarui Lu; Xiaoyin Chen; Stephen Zhewen Lu; Chence Shi; Hongyu Guo; Yoshua Bengio; Jian Tang 005 (ICLR, 2025)