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Chence Shi
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2020 – today
- 2022
- [i10]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:
TorchDrug: A Powerful and Flexible Machine Learning Platform for Drug Discovery. CoRR abs/2202.08320 (2022) - [i9]Minkai Xu, Lantao Yu, Yang Song, Chence Shi, Stefano Ermon, Jian Tang:
GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation. CoRR abs/2203.02923 (2022) - 2021
- [c8]Yutong Xie, Chence Shi, Hao Zhou, Yuwei Yang, Weinan Zhang, Yong Yu, Lei Li:
MARS: Markov Molecular Sampling for Multi-objective Drug Discovery. ICLR 2021 - [c7]Hangrui Bi, Hengyi Wang, Chence Shi, Connor W. Coley, Jian Tang, Hongyu Guo:
Non-Autoregressive Electron Redistribution Modeling for Reaction Prediction. ICML 2021: 904-913 - [c6]Chence Shi, Shitong Luo, Minkai Xu, Jian Tang:
Learning Gradient Fields for Molecular Conformation Generation. ICML 2021: 9558-9568 - [c5]Minkai Xu, Wujie Wang, Shitong Luo, Chence Shi, Yoshua Bengio, Rafael Gómez-Bombarelli, Jian Tang:
An End-to-End Framework for Molecular Conformation Generation via Bilevel Programming. ICML 2021: 11537-11547 - [c4]Shitong Luo, Chence Shi, Minkai Xu, Jian Tang:
Predicting Molecular Conformation via Dynamic Graph Score Matching. NeurIPS 2021: 19784-19795 - [i8]Yutong Xie, Chence Shi, Hao Zhou, Yuwei Yang, Weinan Zhang, Yong Yu, Lei Li:
MARS: Markov Molecular Sampling for Multi-objective Drug Discovery. CoRR abs/2103.10432 (2021) - [i7]Chence Shi, Shitong Luo, Minkai Xu, Jian Tang:
Learning Gradient Fields for Molecular Conformation Generation. CoRR abs/2105.03902 (2021) - [i6]Minkai Xu, Wujie Wang, Shitong Luo, Chence Shi, Yoshua Bengio, Rafael Gómez-Bombarelli
, Jian Tang:
An End-to-End Framework for Molecular Conformation Generation via Bilevel Programming. CoRR abs/2105.07246 (2021) - [i5]Hangrui Bi, Hengyi Wang, Chence Shi, Connor W. Coley, Jian Tang, Hongyu Guo:
Non-Autoregressive Electron Redistribution Modeling for Reaction Prediction. CoRR abs/2106.07801 (2021) - 2020
- [c3]Chence Shi, Minkai Xu, Zhaocheng Zhu, Weinan Zhang, Ming Zhang, Jian Tang:
GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation. ICLR 2020 - [c2]Chence Shi, Minkai Xu, Hongyu Guo, Ming Zhang, Jian Tang:
A Graph to Graphs Framework for Retrosynthesis Prediction. ICML 2020: 8818-8827 - [i4]Chence Shi, Minkai Xu, Zhaocheng Zhu, Weinan Zhang, Ming Zhang, Jian Tang:
GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation. CoRR abs/2001.09382 (2020) - [i3]Chence Shi, Minkai Xu, Hongyu Guo, Ming Zhang, Jian Tang:
A Graph to Graphs Framework for Retrosynthesis Prediction. CoRR abs/2003.12725 (2020) - [i2]Hangrui Bi, Hengyi Wang, Chence Shi, Jian Tang:
Non-autoregressive electron flow generation for reaction prediction. CoRR abs/2012.12124 (2020)
2010 – 2019
- 2019
- [c1]Weiping Song, Chence Shi, Zhiping Xiao
, Zhijian Duan, Yewen Xu, Ming Zhang, Jian Tang:
AutoInt: Automatic Feature Interaction Learning via Self-Attentive Neural Networks. CIKM 2019: 1161-1170 - 2018
- [i1]Weiping Song, Chence Shi, Zhiping Xiao, Zhijian Duan, Yewen Xu, Ming Zhang, Jian Tang:
AutoInt: Automatic Feature Interaction Learning via Self-Attentive Neural Networks. CoRR abs/1810.11921 (2018)
Coauthor Index

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