Shuxin Zheng

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 48

Top Topics

Structural Motifs

Top Venues

Publications

He Zhang, Siyuan Liu, Jiacheng You, Chang Liu, Shuxin Zheng, Ziheng Lu, Tong Wang, Nanning Zheng, Bin Shao
Overcoming the barrier of orbital-free density functional theory for molecular systems using deep learning. Nat. Comput. Sci. 4 (3) (2024)
Tianlang Chen, Shengjie Luo, Di He, Shuxin Zheng, Tie-Yan Liu, Liwei Wang
GeoMFormer: A General Architecture for Geometric Molecular Representation Learning. CoRR (2024)
Haoxiang Guan, Jiyan He, Shuxin Zheng, En-Hong Chen, Weiming Zhang, Nenghai Yu
Towards Generalist Prompting for Large Language Models by Mental Models. CoRR (2024)
Shuxin Zheng, Sai Liang, Chunyun Meng, Zhongguo Zhang, Li Luan
A Cross-Period Network for Clothing Change Person Re-Identification. IEEE Access 12 (2024)
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
Predicting equilibrium distributions for molecular systems with deep learning. Nat. Mac. Intell. 6 (5) (2024)
He Zhang, Siyuan Liu, Jiacheng You, Chang Liu, Shuxin Zheng, Ziheng Lu, Tong Wang, Nanning Zheng, Bin Shao
M-OFDFT: Overcoming the Barrier of Orbital-Free Density Functional Theory for Molecular Systems Using Deep Learning. CoRR (2023)
Shengjie Luo, Tianlang Chen, Yixian Xu, Shuxin Zheng, Tie-Yan Liu, Liwei Wang, Di He
One Transformer Can Understand Both 2D & 3D Molecular Data. ICLR (2023)
Mingqing Xiao, Shuxin Zheng, Chang Liu, Zhouchen Lin, Tie-Yan Liu
Invertible Rescaling Network and Its Extensions. Int. J. Comput. Vis. 131 (1) (2023)
Cuicui Peng, Yunjie Zhang, Shuxin Zheng
A New Enhanced Tensor Low Rank Representation Method for Image Denoising. ICCIP (2023)
Jiyan He, Weitao Feng, Yaosen Min, Jingwei Yi, Kunsheng Tang, Shuai Li, Jie Zhang, Kejiang Chen, Wenbo Zhou, Xing Xie, Weiming Zhang, Nenghai Yu, Shuxin Zheng
Control Risk for Potential Misuse of Artificial Intelligence in Science. CoRR (2023)
Yiwen Zheng, Prakash Thakolkaran, Jake A. Smith, Ziheng Lu, Shuxin Zheng, Bichlien H. Nguyen, Siddhant Kumar, Aniruddh Vashisth
Inverse Design of Vitrimeric Polymers by Molecular Dynamics and Generative Modeling. CoRR (2023)
Shuxin Zheng, Zhongguo Zhang
Adaptive tourism forecasting using hybrid artificial intelligence model: a case study of Xi'an international tourist arrivals. PeerJ Comput. Sci. 9 (2023)
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
Towards Predicting Equilibrium Distributions for Molecular Systems with Deep Learning. CoRR (2023)
Zaixi Zhang, Yaosen Min, Shuxin Zheng, Qi Liu
Molecule Generation For Target Protein Binding with Structural Motifs. ICLR (2023)
Yu Shi, Guolin Ke, Zhuoming Chen, Shuxin Zheng, Tie-Yan Liu
Quantized Training of Gradient Boosting Decision Trees. NeurIPS (2022)
Peng Ren, Xingyue Liu, Shuxin Zheng, Lijun Liao, Xin Li, Ligong Lu, Xia Wang, Ruoyu Wang, Ming Sheng
A Hybrid Medical Causal Inference Platform Based on Data Lake. HIS (2022)
Yu Shi, Shuxin Zheng, Guolin Ke, Yifei Shen, Jiacheng You, Jiyan He, Shengjie Luo, Chang Liu, Di He, Tie-Yan Liu
Benchmarking Graphormer on Large-Scale Molecular Modeling Datasets. CoRR (2022)
Shengjie Luo, Shanda Li, Shuxin Zheng, Tie-Yan Liu, Liwei Wang, Di He
Your Transformer May Not be as Powerful as You Expect. NeurIPS (2022)
Yu Shi, Guolin Ke, Zhuoming Chen, Shuxin Zheng, Tie-Yan Liu
Quantized Training of Gradient Boosting Decision Trees. CoRR (2022)
Shengjie Luo, Tianlang Chen, Yixian Xu, Shuxin Zheng, Tie-Yan Liu, Di He, Liwei Wang
One Transformer Can Understand Both 2D & 3D Molecular Data. CoRR (2022)
Mingqing Xiao, Shuxin Zheng, Chang Liu, Zhouchen Lin, Tie-Yan Liu
Invertible Rescaling Network and Its Extensions. CoRR (2022)
Shengjie Luo, Shanda Li, Shuxin Zheng, Tie-Yan Liu, Liwei Wang, Di He
Your Transformer May Not be as Powerful as You Expect. CoRR (2022)
Yaosen Min, Ye Wei, Peizhuo Wang, Nian Wu, Stefan Bauer, Shuxin Zheng, Yu Shi, Yingheng Wang, Dan Zhao, Ji Wu, Jianyang Zeng
Predicting the protein-ligand affinity from molecular dynamics trajectories. CoRR (2022)
Dinglan Peng, Shuxin Zheng, Yatao Li, Guolin Ke, Di He, Tie-Yan Liu
How could Neural Networks understand Programs? ICML (2021)
Chengxuan Ying, Tianle Cai, Shengjie Luo, Shuxin Zheng, Guolin Ke, Di He, Yanming Shen, Tie-Yan Liu
Do Transformers Really Perform Badly for Graph Representation? NeurIPS (2021)
Chengxuan Ying, Tianle Cai, Shengjie Luo, Shuxin Zheng, Guolin Ke, Di He, Yanming Shen, Tie-Yan Liu
Do Transformers Really Perform Bad for Graph Representation? CoRR (2021)
Shengjie Luo, Shanda Li, Tianle Cai, Di He, Dinglan Peng, Shuxin Zheng, Guolin Ke, Liwei Wang, Tie-Yan Liu
Stable, Fast and Accurate: Kernelized Attention with Relative Positional Encoding. NeurIPS (2021)
Shengjie Luo, Shanda Li, Tianle Cai, Di He, Dinglan Peng, Shuxin Zheng, Guolin Ke, Liwei Wang, Tie-Yan Liu
Stable, Fast and Accurate: Kernelized Attention with Relative Positional Encoding. CoRR (2021)
Zhuliang Yao, Yue Cao, Shuxin Zheng, Gao Huang, Stephen Lin
Cross-Iteration Batch Normalization. CVPR (2021)
Abhishek Das, Muhammed Shuaibi, Aini Palizhati, Siddharth Goyal, Aditya Grover, Adeesh Kolluru, Janice Lan, Ammar Rizvi, Anuroop Sriram, Brandon M. Wood, Devi Parikh, Zachary W. Ulissi, C. Lawrence Zitnick, Guolin Ke, Shuxin Zheng, Yu Shi, Di He, Tie-Yan Liu, Chengxuan Ying, Jiacheng You, Yihan He, Rostislav Grigoriev, Ruslan Lukin, Adel Yarullin, Max Faleev
The Open Catalyst Challenge 2021: Competition Report. NeurIPS (Competition and Demos) (2021)
Dinglan Peng, Shuxin Zheng, Yatao Li, Guolin Ke, Di He, Tie-Yan Liu
How could Neural Networks understand Programs? CoRR (2021)
Shengjie Luo, Kaiyuan Gao, Shuxin Zheng, Guolin Ke, Di He, Liwei Wang, Tie-Yan Liu
Revisiting Language Encoding in Learning Multilingual Representations. CoRR (2021)
Chengxuan Ying, Mingqi Yang, Shuxin Zheng, Guolin Ke, Shengjie Luo, Tianle Cai, Chenglin Wu, Yuxin Wang, Yanming Shen, Di He
First Place Solution of KDD Cup 2021 & OGB Large-Scale Challenge Graph Prediction Track. CoRR (2021)
Mingqing Xiao, Shuxin Zheng, Chang Liu, Yaolong Wang, Di He, Guolin Ke, Jiang Bian, Zhouchen Lin, Tie-Yan Liu
Invertible Image Rescaling. CoRR (2020)
Yaolong Wang, Mingqing Xiao, Chang Liu, Shuxin Zheng, Tie-Yan Liu
Modeling Lost Information in Lossy Image Compression. CoRR (2020)
Zhuliang Yao, Yue Cao, Shuxin Zheng, Gao Huang, Stephen Lin
Cross-Iteration Batch Normalization. CoRR (2020)
Zhenhui Xu, Linyuan Gong, Guolin Ke, Di He, Shuxin Zheng, Liwei Wang, Jiang Bian, Tie-Yan Liu
MC-BERT: Efficient Language Pre-Training via a Meta Controller. CoRR (2020)
Ruibin Xiong, Yunchang Yang, Di He, Kai Zheng, Shuxin Zheng, Chen Xing, Huishuai Zhang, Yanyan Lan, Liwei Wang, Tie-Yan Liu
On Layer Normalization in the Transformer Architecture. CoRR (2020)
Mingqing Xiao, Shuxin Zheng, Chang Liu, Yaolong Wang, Di He, Guolin Ke, Jiang Bian, Zhouchen Lin, Tie-Yan Liu
Invertible Image Rescaling. ECCV (1) (2020)
Ruibin Xiong, Yunchang Yang, Di He, Kai Zheng, Shuxin Zheng, Chen Xing, Huishuai Zhang, Yanyan Lan, Liwei Wang, Tie-Yan Liu
On Layer Normalization in the Transformer Architecture. ICML (2020)
Li He, Shuxin Zheng, Wei Chen, Zhiming Ma, Tie-Yan Liu
OptQuant: Distributed training of neural networks with optimized quantization mechanisms. Neurocomputing 340 (2019)
Qi Meng, Shuxin Zheng, Huishuai Zhang, Wei Chen, Qiwei Ye, Zhi-Ming Ma, Nenghai Yu, Tie-Yan Liu
G-SGD: Optimizing ReLU Neural Networks in its Positively Scale-Invariant Space. ICLR (Poster) (2019)
Shuxin Zheng, Qi Meng, Huishuai Zhang, Wei Chen, Nenghai Yu, Tie-Yan Liu
Capacity Control of ReLU Neural Networks by Basis-Path Norm. AAAI (2019)
Dongbao Jia, Shuxin Zheng, Lin Yang, Yuki Todo, Shangce Gao
A Dendritic Neuron Model with Nonlinearity Validation on Istanbul Stock and Taiwan Futures Exchange Indexes Prediction. CCIS (2018)
Shuxin Zheng, Qi Meng, Huishuai Zhang, Wei Chen, Nenghai Yu, Tie-Yan Liu
Capacity Control of ReLU Neural Networks by Basis-path Norm. CoRR (2018)
Qi Meng, Wei Chen, Shuxin Zheng, Qiwei Ye, Tie-Yan Liu
Optimizing Neural Networks in the Equivalent Class Space. CoRR (2018)
Shuxin Zheng, Qi Meng, Taifeng Wang, Wei Chen, Nenghai Yu, Zhiming Ma, Tie-Yan Liu
Asynchronous Stochastic Gradient Descent with Delay Compensation. ICML (2017)
Shuxin Zheng, Qi Meng, Taifeng Wang, Wei Chen, Nenghai Yu, Zhiming Ma, Tie-Yan Liu
Asynchronous Stochastic Gradient Descent with Delay Compensation for Distributed Deep Learning. CoRR (2016)