Yu Shi

Scalable emulation of protein equilibrium ensembles with generative deep learning

Sarah Lewis, Tim Hempel, Jose Jimenez-Luna, Michael Gastegger, Yu Xie, Andrew Y. K. Foong, Victor Garcia Satorras, Osama Abdin, Bastiaan S. Veeling, I. Zaporozhets, Yaoyi Chen, Soojung Yang, Arne Schneuing, Jigyasa Nigam, Federico Barbero, Vincent Stimper, Andrew Campbell, Jason Yim, Marten Lienen, Yu Shi, Shuxin Zheng, Hannes Schulz, Usman Munir, Cecilia Clementi, Frank Noé

December 2024

Preprint

Physical Consistency Bridges Heterogeneous Data in Molecular Multi-Task Learning

Yuxuan Ren, Dihan Zheng, Chang Liu, Peiran Jin, Yu Shi, Lin Huang, Jiyan He, Shengjie Luo, Tao Qin, Tie-Yan Liu

2024 Neural Information Processing Systems | October 2024

Publication Preprint

Towards Predicting Equilibrium Distributions for Molecular Systems with Deep Learning

Shuxin Zheng, Jiyan He, Chang Liu, Yu Shi, Ziheng Lu, Weitao Feng, Fusong Ju, Jiaxi Wang, Jianwei Zhu, Yaosen Min, He Zhang, Shidi Tang, Hongxia Hao, Peiran Jin, Chi Chen, Frank Noé, Haiguang Liu, Tie-Yan Liu

June 2023

Publication Vidéo

Quantized Training of Gradient Boosting Decision Trees

Yu Shi, Guolin Ke, Zhuoming Chen, Shuxin Zheng, Tie-Yan Liu

2022 Neural Information Processing Systems | November 2022

Publication

Gradient Boosting With Piece-Wise Linear Regression Trees

Yu Shi, Jian Li, Zhize Li

2019 International Joint Conference on Artificial Intelligence | July 2019

Publication DOI

Scalable emulation of protein equilibrium ensembles with generative deep learning

Sarah Lewis, Tim Hempel, Jose Jimenez-Luna, Michael Gastegger, Yu Xie, Andrew Y. K. Foong, Victor Garcia Satorras, Osama Abdin, Bastiaan S. Veeling, I. Zaporozhets, Yaoyi Chen, Soojung Yang, Arne Schneuing, Jigyasa Nigam, Federico Barbero, Vincent Stimper, Andrew Campbell, Jason Yim, Marten Lienen, Yu Shi, Shuxin Zheng, Hannes Schulz, Usman Munir, Cecilia Clementi, Frank Noé

December 2024

Preprint

Physical Consistency Bridges Heterogeneous Data in Molecular Multi-Task Learning

Yuxuan Ren, Dihan Zheng, Chang Liu, Peiran Jin, Yu Shi, Lin Huang, Jiyan He, Shengjie Luo, Tao Qin, Tie-Yan Liu

2024 Neural Information Processing Systems | October 2024

Publication Preprint

Towards Predicting Equilibrium Distributions for Molecular Systems with Deep Learning

Shuxin Zheng, Jiyan He, Chang Liu, Yu Shi, Ziheng Lu, Weitao Feng, Fusong Ju, Jiaxi Wang, Jianwei Zhu, Yaosen Min, He Zhang, Shidi Tang, Hongxia Hao, Peiran Jin, Chi Chen, Frank Noé, Haiguang Liu, Tie-Yan Liu

June 2023

Publication Vidéo

Quantized Training of Gradient Boosting Decision Trees

Yu Shi, Guolin Ke, Zhuoming Chen, Shuxin Zheng, Tie-Yan Liu

2022 Neural Information Processing Systems | November 2022

Publication

Gradient Boosting With Piece-Wise Linear Regression Trees

Yu Shi, Jian Li, Zhize Li

2019 International Joint Conference on Artificial Intelligence | July 2019

Publication DOI

Scalable emulation of protein equilibrium ensembles with generative deep learning

Sarah Lewis, Tim Hempel, Jose Jimenez-Luna, Michael Gastegger, Yu Xie, Andrew Y. K. Foong, Victor Garcia Satorras, Osama Abdin, Bastiaan S. Veeling, I. Zaporozhets, Yaoyi Chen, Soojung Yang, Arne Schneuing, Jigyasa Nigam, Federico Barbero, Vincent Stimper, Andrew Campbell, Jason Yim, Marten Lienen, Yu Shi, Shuxin Zheng, Hannes Schulz, Usman Munir, Cecilia Clementi, Frank Noé

December 2024

Preprint

Physical Consistency Bridges Heterogeneous Data in Molecular Multi-Task Learning

Yuxuan Ren, Dihan Zheng, Chang Liu, Peiran Jin, Yu Shi, Lin Huang, Jiyan He, Shengjie Luo, Tao Qin, Tie-Yan Liu

2024 Neural Information Processing Systems | October 2024

Publication Preprint

Quantized Training of Gradient Boosting Decision Trees

Yu Shi, Guolin Ke, Zhuoming Chen, Shuxin Zheng, Tie-Yan Liu

2022 Neural Information Processing Systems | November 2022

Publication

Gradient Boosting With Piece-Wise Linear Regression Trees

Yu Shi, Jian Li, Zhize Li

2019 International Joint Conference on Artificial Intelligence | July 2019

Publication DOI

Towards Predicting Equilibrium Distributions for Molecular Systems with Deep Learning

Shuxin Zheng, Jiyan He, Chang Liu, Yu Shi, Ziheng Lu, Weitao Feng, Fusong Ju, Jiaxi Wang, Jianwei Zhu, Yaosen Min, He Zhang, Shidi Tang, Hongxia Hao, Peiran Jin, Chi Chen, Frank Noé, Haiguang Liu, Tie-Yan Liu

June 2023

Publication Vidéo