Chence Shi

According to our database, Chence Shi authored at least 14 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Fusing Neural and Physical: Augment Protein Conformation Sampling with Tractable Simulations.

Jiarui Lu, Zuobai Zhang, Bozitao Zhong, Chence Shi, Jian Tang

CoRR, 2024

2023

E3Bind: An End-to-End Equivariant Network for Protein-Ligand Docking.

Yangtian Zhang, Huiyu Cai, Chence Shi, Jian Tang

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Protein Sequence and Structure Co-Design with Equivariant Translation.

Chence Shi, Chuanrui Wang, Jiarui Lu, Bozitao Zhong, Jian Tang

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

E3Bind: An End-to-End Equivariant Network for Protein-Ligand Docking.

Yangtian Zhang, Huiyu Cai, Chence Shi, Bozitao Zhong, Jian Tang

CoRR, 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, Junkun Chen, Huiyu Cai, Jiarui Lu, Chang Ma, Runcheng Liu, Louis-Pascal A. C. Xhonneux, Meng Qu, Jian Tang

CoRR, 2022

GeoDiff: A Geometric Diffusion Model for Molecular Conformation Generation.

Minkai Xu, Lantao Yu, Yang Song, Chence Shi, Stefano Ermon, Jian Tang

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Predicting Molecular Conformation via Dynamic Graph Score Matching.

Shitong Luo, Chence Shi, Minkai Xu, Jian Tang

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 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

Proceedings of the 38th International Conference on Machine Learning, 2021

Learning Gradient Fields for Molecular Conformation Generation.

Chence Shi, Shitong Luo, Minkai Xu, Jian Tang

Proceedings of the 38th International Conference on Machine Learning, 2021

Non-Autoregressive Electron Redistribution Modeling for Reaction Prediction.

Hangrui Bi, Hengyi Wang, Chence Shi, Connor W. Coley, Jian Tang, Hongyu Guo

Proceedings of the 38th International Conference on Machine Learning, 2021

MARS: Markov Molecular Sampling for Multi-objective Drug Discovery.

Yutong Xie, Chence Shi, Hao Zhou, Yuwei Yang, Weinan Zhang, Yong Yu, Lei Li

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

A Graph to Graphs Framework for Retrosynthesis Prediction.

Chence Shi, Minkai Xu, Hongyu Guo, Ming Zhang, Jian Tang

Proceedings of the 37th International Conference on Machine Learning, 2020

GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation.

Chence Shi, Minkai Xu, Zhaocheng Zhu, Weinan Zhang, Ming Zhang, Jian Tang

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

AutoInt: Automatic Feature Interaction Learning via Self-Attentive Neural Networks.

Weiping Song, Chence Shi, Zhiping Xiao, Zhijian Duan, Yewen Xu, Ming Zhang, Jian Tang

Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019