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2020 – today
- 2024
[j6]Shuxin Zheng, Sai Liang, Chunyun Meng, Zhongguo Zhang, Li Luan:
A Cross-Period Network for Clothing Change Person Re-Identification. IEEE Access 12: 53517-53532 (2024)- [j5]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): 558-567 (2024) - [j4]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): 210-223 (2024) - [c18]Tianlang Chen, Shengjie Luo, Di He, Shuxin Zheng, Tie-Yan Liu, Liwei Wang:
GeoMFormer: A General Architecture for Geometric Molecular Representation Learning. ICML 2024 - [i25]Haoxiang Guan, Jiyan He, Shuxin Zheng, En-Hong Chen, Weiming Zhang, Nenghai Yu:
Towards Generalist Prompting for Large Language Models by Mental Models. CoRR abs/2402.18252 (2024) - [i24]Tianlang Chen, Shengjie Luo, Di He, Shuxin Zheng, Tie-Yan Liu, Liwei Wang:
GeoMFormer: A General Architecture for Geometric Molecular Representation Learning. CoRR abs/2406.16853 (2024) - 2023
- [j3]Mingqing Xiao, Shuxin Zheng, Chang Liu, Zhouchen Lin, Tie-Yan Liu:
Invertible Rescaling Network and Its Extensions. Int. J. Comput. Vis. 131(1): 134-159 (2023) - [j2]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: e1573 (2023) - [c17]Cuicui Peng, Yunjie Zhang, Shuxin Zheng:
A New Enhanced Tensor Low Rank Representation Method for Image Denoising. ICCIP 2023: 213-220 - [c16]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 - [c15]Zaixi Zhang, Yaosen Min, Shuxin Zheng, Qi Liu:
Molecule Generation For Target Protein Binding with Structural Motifs. ICLR 2023 - [i23]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 abs/2306.05445 (2023) - [i22]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 abs/2309.16578 (2023) - [i21]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 abs/2312.03690 (2023) - [i20]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 abs/2312.06632 (2023) - 2022
- [c14]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: 136-144 - [c13]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 - [c12]Yu Shi, Guolin Ke, Zhuoming Chen, Shuxin Zheng, Tie-Yan Liu:
Quantized Training of Gradient Boosting Decision Trees. NeurIPS 2022 - [i19]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 abs/2203.04810 (2022) - [i18]Shengjie Luo, Shanda Li, Shuxin Zheng, Tie-Yan Liu, Liwei Wang, Di He:
Your Transformer May Not be as Powerful as You Expect. CoRR abs/2205.13401 (2022) - [i17]Yu Shi, Guolin Ke, Zhuoming Chen, Shuxin Zheng, Tie-Yan Liu:
Quantized Training of Gradient Boosting Decision Trees. CoRR abs/2207.09682 (2022) - [i16]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 abs/2208.10230 (2022) - [i15]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 abs/2210.01765 (2022) - [i14]Mingqing Xiao, Shuxin Zheng, Chang Liu, Zhouchen Lin, Tie-Yan Liu:
Invertible Rescaling Network and Its Extensions. CoRR abs/2210.04188 (2022) - 2021
- [c11]Zhuliang Yao, Yue Cao, Shuxin Zheng, Gao Huang, Stephen Lin:
Cross-Iteration Batch Normalization. CVPR 2021: 12331-12340 - [c10]Dinglan Peng, Shuxin Zheng, Yatao Li, Guolin Ke, Di He, Tie-Yan Liu:
How could Neural Networks understand Programs? ICML 2021: 8476-8486 - [c9]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: 29-40 - [c8]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: 22795-22807 - [c7]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: 28877-28888 - [i13]Shengjie Luo, Kaiyuan Gao, Shuxin Zheng, Guolin Ke, Di He, Liwei Wang, Tie-Yan Liu:
Revisiting Language Encoding in Learning Multilingual Representations. CoRR abs/2102.08357 (2021) - [i12]Dinglan Peng, Shuxin Zheng, Yatao Li, Guolin Ke, Di He, Tie-Yan Liu:
How could Neural Networks understand Programs? CoRR abs/2105.04297 (2021) - [i11]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 abs/2106.05234 (2021) - [i10]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 abs/2106.08279 (2021) - [i9]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 abs/2106.12566 (2021) - 2020
- [c6]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: 126-144 - [c5]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: 10524-10533 - [i8]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 abs/2002.04745 (2020) - [i7]Zhuliang Yao, Yue Cao, Shuxin Zheng, Gao Huang, Stephen Lin:
Cross-Iteration Batch Normalization. CoRR abs/2002.05712 (2020) - [i6]Mingqing Xiao, Shuxin Zheng, Chang Liu, Yaolong Wang, Di He, Guolin Ke, Jiang Bian, Zhouchen Lin, Tie-Yan Liu:
Invertible Image Rescaling. CoRR abs/2005.05650 (2020) - [i5]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 abs/2006.05744 (2020) - [i4]Yaolong Wang, Mingqing Xiao, Chang Liu, Shuxin Zheng, Tie-Yan Liu:
Modeling Lost Information in Lossy Image Compression. CoRR abs/2006.11999 (2020)
2010 – 2019
- 2019
- [j1]Li He, Shuxin Zheng, Wei Chen, Zhiming Ma, Tie-Yan Liu:
OptQuant: Distributed training of neural networks with optimized quantization mechanisms. Neurocomputing 340: 233-244 (2019) - [c4]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: 5925-5932 - [c3]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 - 2018
- [c2]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: 242-246 - [i3]Qi Meng, Wei Chen, Shuxin Zheng, Qiwei Ye, Tie-Yan Liu:
Optimizing Neural Networks in the Equivalent Class Space. CoRR abs/1802.03713 (2018) - [i2]Shuxin Zheng, Qi Meng, Huishuai Zhang, Wei Chen, Nenghai Yu, Tie-Yan Liu:
Capacity Control of ReLU Neural Networks by Basis-path Norm. CoRR abs/1809.07122 (2018) - 2017
- [c1]Shuxin Zheng, Qi Meng, Taifeng Wang, Wei Chen, Nenghai Yu, Zhiming Ma, Tie-Yan Liu:
Asynchronous Stochastic Gradient Descent with Delay Compensation. ICML 2017: 4120-4129 - 2016
- [i1]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 abs/1609.08326 (2016)
Coauthor Index
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last updated on 2024-10-07 21:19 CEST by the dblp team
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