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ORCIDWeinan E
鄂维南;
Person information
- unicode name: 鄂维南;
- affiliation: Beijing Institute of Big Data Research, China
- affiliation: Princeton University, Department of Mathematics, NJ, USA
- affiliation: Peking University, China
- award: Presidential Early Career Award for Scientists and Engineers
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2020 – today
- 2026
[i103]Yuheng Wang, Runde Yang, Lin Wu, Jie Zhang, Jingru Fan, Ruoyu Fu, Tianle Zhou, Huatao Li, Siheng Chen, Weinan E, Chen Qian:
Generative Teaching via Code. CoRR abs/2601.04204 (2026)- [i102]Xinyu Zhu, Yuzhu Cai, Zexi Liu, Bingyang Zheng, Cheng Wang, Rui Ye, Jiaao Chen, Hanrui Wang, Wei-Chen Wang, Yuzhi Zhang, Linfeng Zhang, Weinan E, Di Jin, Siheng Chen, Yanfeng Wang:
Toward Ultra-Long-Horizon Agentic Science: Cognitive Accumulation for Machine Learning Engineering. CoRR abs/2601.10402 (2026) - [i101]Yongqi Jin, Yecheng Wang, Junjie Wang, Rong Zhu, Guolin Ke, Weinan E:
From Human Labels to Literature: Semi-Supervised Learning of NMR Chemical Shifts at Scale. CoRR abs/2601.18524 (2026) - [i100]Zichen Wen, Boxue Yang, Shuang Chen, Yaojie Zhang, Yuhang Han, Junlong Ke, Cong Wang, Yicheng Fu, Jiawang Zhao, Jiangchao Yao, Xi Fang, Zhen Wang, Henxing Cai, Lin Yao, Zhifeng Gao, Yanhui Hong, Nang Yuan, Yixuan Li, Guojiang Zhao, Haoyi Tao, Nan Wang, Han Lyu, Guolin Ke, Ning Liao, Xiaoxing Wang, Kai Chen, Zhiyu Li, Feiyu Xiong, Sihan Hu, Kun Chen, Yanfeng Wang, Weinan E:
Innovator-VL: A Multimodal Large Language Model for Scientific Discovery. CoRR abs/2601.19325 (2026) - [i99]Yucheng Liao, Han Wen, Weinan E, Weijie Zhang:
DIA-CLIP: a universal representation learning framework for zero-shot DIA proteomics. CoRR abs/2602.01772 (2026) - [i98]Yuzhi Liu, Duo Zhang, Anyang Peng, Weinan E, Linfeng Zhang, Han Wang:
Scaling Machine Learning Interatomic Potentials with Mixtures of Experts. CoRR abs/2603.07977 (2026) - [i97]Hao Liang, Zhengyang Zhao, Zhaoyang Han, Meiyi Qiang, Xiaochen Ma, Bohan Zeng, Qifeng Cai, Zhiyu Li, Linpeng Tang, Weinan E, Wentao Zhang:
Towards Next-Generation LLM Training: From the Data-Centric Perspective. CoRR abs/2603.14712 (2026) - [i96]Hao Liang, Zhengyang Zhao, Meiyi Qiang, Mingrui Chen, Lu Ma, Rongyi Yu, Hengyi Feng, Shixuan Sun, Zimo Meng, Xiaochen Ma, Xuanlin Yang, Qifeng Cai, Ruichuan An, Bohan Zeng, Zhen Hao Wong, Chengyu Shen, Runming He, Zhaoyang Han, Yaowei Zheng, Fangcheng Fu, Conghui He, Bin Cui, Zhiyu Li, Weinan E, Wentao Zhang:
DataFlex: A Unified Framework for Data-Centric Dynamic Training of Large Language Models. CoRR abs/2603.26164 (2026) - [i95]Tingjia Miao, Wenkai Jin, Muhua Zhang, Jinxin Tan, Yuelin Hu, Tu Guo, Jiejun Zhang, Yuhan Wang, Wenbo Li, Yinuo Gao, Shuo Chen, Weiqi Jiang, Yayun Hu, Zixing Lei, Xianghe Pang, Zexi Liu, Yuzhi Zhang, Linfeng Zhang, Kun Chen, Wei Wang, Weinan E, Siheng Chen:
PRL-Bench: A Comprehensive Benchmark Evaluating LLMs' Capabilities in Frontier Physics Research. CoRR abs/2604.15411 (2026) - [i94]Xinyu Zhu, Yuzhu Cai, Zexi Liu, Cheng Wang, Fengyang Li, Wenkai Jin, Wanxu Liu, Zehao Bing, Bingyang Zheng, Jingyi Chai, Shuo Tang, Rui Ye, Yuwen Du, Xianghe Pang, Yaxin Du, Tingjia Miao, Yuzhi Zhang, Ruoxue Liao, Zhaohan Ding, Linfeng Zhang, Yanfeng Wang, Weinan E, Siheng Chen:
EvoMaster: A Foundational Evolving Agent Framework for Agentic Science at Scale. CoRR abs/2604.17406 (2026) - 2025
- [j35]Wei Hu, Jihao Long, Yaohua Zang
, Weinan E, Jiequn Han:
Solving optimal control problems of rigid-body dynamics with collisions using the hybrid minimum principle. Commun. Nonlinear Sci. Numer. Simul. 143: 108603 (2025) - [j34]Junjie Yao, Yuxiao Yi, Liangkai Hang, Weinan E, Weizong Wang, Yaoyu Zhang, Tianhan Zhang, Zhi-Qin John Xu:
Solving multiscale dynamical systems by deep learning. Comput. Phys. Commun. 316: 109802 (2025) - [j33]Fanjie Xu, Wentao Guo, Feng Wang, Lin Yao, Hongshuai Wang, Fujie Tang, Zhifeng Gao, Linfeng Zhang, Weinan E, Zhong-Qun Tian, Jun Cheng:
Toward a unified benchmark and framework for deep learning-based prediction of nuclear magnetic resonance chemical shifts. Nat. Comput. Sci. 5(4): 292-300 (2025) - [c26]Yichen He, Guanhua Huang, Peiyuan Feng, Yuan Lin, Yuchen Zhang, Hang Li, Weinan E:
PaSa: An LLM Agent for Comprehensive Academic Paper Search. ACL (1) 2025: 11663-11679 - [c25]Wei Hu, Yue Zhao, Weinan E, Jiequn Han, Jihao Long:
Learning Free Terminal Time Optimal Closed-loop Control of Manipulators. ACC 2025: 127-133 - [c24]Jinbo Wang, Mingze Wang, Zhanpeng Zhou, Junchi Yan, Weinan E, Lei Wu:
The Sharpness Disparity Principle in Transformers for Accelerating Language Model Pre-Training. ICML 2025 - [c23]Mingze Wang, Weinan E:
On the Expressive Power of Mixture-of-Experts for Structured Complex Tasks. NeurIPS 2025 - [i93]Yichen He, Guanhua Huang, Peiyuan Feng, Yuan Lin, Yuchen Zhang, Hang Li, Weinan E:
PaSa: An LLM Agent for Comprehensive Academic Paper Search. CoRR abs/2501.10120 (2025) - [i92]Yingying Sun, Jun A, Zhiwei Liu, Rui Sun, Liujia Qian, Samuel H. Payne, Wout Bittremieux, Markus Ralser, Chen Li, Yi Chen, Zhen Dong, Yasset Pérez-Riverol, Asif Khan, Chris Sander, Ruedi Aebersold, Juan Antonio Vizcaíno, Jonathan R. Krieger, Jianhua Yao, Han Wen, Linfeng Zhang, Yunping Zhu, Yue Xuan, Benjamin Boyang Sun, Liang Qiao, Henning Hermjakob, Haixu Tang, Huanhuan Gao, Yamin Deng, Qing Zhong, Cheng Chang, Nuno Bandeira, Ming Li, Weinan E, Siqi Sun, Yuedong Yang, Gilbert S. Omenn, Yue Zhang, Ping Xu, Yan Fu, Xiaowen Liu, Christopher M. Overall, Yu Wang, Eric W. Deutsch, Luonan Chen, Jürgen Cox, Vadim Demichev, Fuchu He, Jiaxing Huang, Huilin Jin, Chao Liu, Nan Li, Zhongzhi Luan, Jiangning Song, Kaicheng Yu, Wanggen Wan, Tai Wang, Kang Zhang, Le Zhang, Peter A. Bell, Matthias Mann, Bing Zhang, Tiannan Guo:
Strategic priorities for transformative progress in advancing biology with proteomics and artificial intelligence. CoRR abs/2502.15867 (2025) - [i91]Jinbo Wang, Mingze Wang, Zhanpeng Zhou, Junchi Yan, Weinan E, Lei Wu:
The Sharpness Disparity Principle in Transformers for Accelerating Language Model Pre-Training. CoRR abs/2502.19002 (2025) - [i90]Shuqi Lu, Haowei Lin, Lin Yao, Zhifeng Gao, Xiaohong Ji, Weinan E, Linfeng Zhang, Guolin Ke:
Uni-3DAR: Unified 3D Generation and Understanding via Autoregression on Compressed Spatial Tokens. CoRR abs/2503.16278 (2025) - [i89]Zhengren Wang, Jiayang Yu, Dongsheng Ma, Zhe Chen, Yu Wang, Zhiyu Li, Feiyu Xiong, Yanfeng Wang, Weinan E, Linpeng Tang, Wentao Zhang:
RARE: Retrieval-Augmented Reasoning Modeling. CoRR abs/2503.23513 (2025) - [i88]Jiequn Han, Arnulf Jentzen, Weinan E:
A brief review of the Deep BSDE method for solving high-dimensional partial differential equations. CoRR abs/2505.17032 (2025) - [i87]Liangkai Hang, Junjie Yao, Zhiwei Bai, Tianyi Chen, Yang Chen, Rongjie Diao, Hezhou Li, Pengxiao Lin, Zhiwei Wang, Cheng Xu, Zhongwang Zhang, Zhangchen Zhou, Zhiyu Li, Zehao Lin, Kai Chen, Feiyu Xiong, Yaoyu Zhang, Weinan E, Hongkang Yang, Zhi-Qin John Xu:
Scalable Complexity Control Facilitates Reasoning Ability of LLMs. CoRR abs/2505.23013 (2025) - [i86]Mingze Wang, Weinan E:
On the Expressive Power of Mixture-of-Experts for Structured Complex Tasks. CoRR abs/2505.24205 (2025) - [i85]Mingze Wang, Jinbo Wang, Jiaqi Zhang, Wei Wang, Peng Pei, Xunliang Cai, Weinan E, Lei Wu:
GradPower: Powering Gradients for Faster Language Model Pre-Training. CoRR abs/2505.24275 (2025) - [i84]Zexi Liu, Yuzhu Cai, Xinyu Zhu, Yujie Zheng, Runkun Chen, Ying Wen, Yanfeng Wang, Weinan E, Siheng Chen:
ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning. CoRR abs/2506.16499 (2025) - [i83]Jiale Zhao, Pengzhi Mao, Kaifei Wang, Yiming Li, Yaping Peng, Ranfei Chen, Shuqi Lu, Xiaohong Ji, Jiaxiang Ding, Xin Zhang, Yucheng Liao, Weinan E, Weijie Zhang, Han Wen, Hao Chi:
pUniFind: a unified large pre-trained deep learning model pushing the limit of mass spectra interpretation. CoRR abs/2507.00087 (2025) - [i82]Jingyi Chai, Shuo Tang, Rui Ye, Yuwen Du, Xinyu Zhu, Mengcheng Zhou, Yanfeng Wang, Weinan E, Yuzhi Zhang, Linfeng Zhang, Siheng Chen:
SciMaster: Towards General-Purpose Scientific AI Agents, Part I. X-Master as Foundation: Can We Lead on Humanity's Last Exam? CoRR abs/2507.05241 (2025) - [i81]Haitao Lin, Junjie Wang, Zhifeng Gao, Xiaohong Ji, Rong Zhu, Linfeng Zhang, Guolin Ke, Weinan E:
SynBridge: Bridging Reaction States via Discrete Flow for Bidirectional Reaction Prediction. CoRR abs/2507.08475 (2025) - [i80]Yong-Jin Liu, Junjie Wang, Fanjie Xu, Xiaohong Ji, Zhifeng Gao, Linfeng Zhang, Guolin Ke, Rong Zhu, Weinan E:
NMR-Solver: Automated Structure Elucidation via Large-Scale Spectral Matching and Physics-Guided Fragment Optimization. CoRR abs/2509.00640 (2025) - [i79]Yu Li, Yuan Huang, Tao Wang, Caiyu Fan, Xiansheng Cai, Sihan Hu, Xinzijian Liu, Cheng Shi, Mingjun Xu, Zhen Wang, Yan Wang, Xiangqi Jin, Tianhan Zhang, Linfeng Zhang, Lei Wang, Youjin Deng, Pan Zhang, Weijie Sun, Xingyu Li, Weinan E, Linfeng Zhang, Zhiyuan Yao, Kun Chen:
Inverse Knowledge Search over Verifiable Reasoning: Synthesizing a Scientific Encyclopedia from a Long Chains-of-Thought Knowledge Base. CoRR abs/2510.26854 (2025) - [i78]Hao Liang, Xiaochen Ma, Zhou Liu, Zhen Hao Wong, Zhengyang Zhao, Zimo Meng, Runming He, Chengyu Shen, Qifeng Cai, Zhaoyang Han, Meiyi Qiang, Yalin Feng, Tianyi Bai, Zewei Pan, Ziyi Guo, Yizhen Jiang, Jingwen Deng, Qijie You, Peichao Lai, Tianyu Guo, Chi Hsu Tsai, Hengyi Feng, Rui Hu, Wenkai Yu, Junbo Niu, Bohan Zeng, Ruichuan An, Lu Ma, Jihao Huang, Yaowei Zheng, Conghui He, Linpeng Tang, Bin Cui, Weinan E, Wentao Zhang:
DataFlow: An LLM-Driven Framework for Unified Data Preparation and Workflow Automation in the Era of Data-Centric AI. CoRR abs/2512.16676 (2025) - [i77]Tingjia Miao, Jiawen Dai, Jingkun Liu, Jinxin Tan, Muhua Zhang, Wenkai Jin, Yuwen Du, Tian Jin, Xianghe Pang, Zexi Liu, Tu Guo, Zhengliang Zhang, Yunjie Huang, Shuo Chen, Rui Ye, Yuzhi Zhang, Linfeng Zhang, Kun Chen, Wei Wang, Weinan E, Siheng Chen:
PhysMaster: Building an Autonomous AI Physicist for Theoretical and Computational Physics Research. CoRR abs/2512.19799 (2025) - [i76]Linfeng Zhang, Siheng Chen, Yuzhu Cai, Jingyi Chai, Junhan Chang, Kun Chen, Zhi X. Chen, Zhaohan Ding, Yuwen Du, Yuanpeng Gao, Yuan Gao, Jing Gao, Zhifeng Gao, Qiangqiang Gu, Yanhui Hong, Yuan Huang, Xi Fang, Xiaohong Ji, Guolin Ke, Zixing Lei, Xinyu Li, Yongge Li, Ruoxue Liao, Hang Lin, Xiaolu Lin, Yuxiang Liu, Xinzijian Liu, Zexi Liu, Jintan Lu, Tingjia Miao, Haohui Que, Weijie Sun, Yanfeng Wang, Bingyang Wu, Tianju Xue, Rui Ye, Jinzhe Zeng, Duo Zhang, Jiahui Zhang, Linfeng Zhang, Tianhan Zhang, Wenchang Zhang, Yuzhi Zhang, Zezhong Zhang, Hang Zheng, Hui Zhou, Tong Zhu, Xinyu Zhu, Qingguo Zhou, Weinan E:
Bohrium + SciMaster: Building the Infrastructure and Ecosystem for Agentic Science at Scale. CoRR abs/2512.20469 (2025) - 2024
- [j32]Jiahao Fan, Ziyao Li, Eric Alcaide, Guolin Ke, Huaqing Huang, Weinan E:
Accurate Conformation Sampling via Protein Structural Diffusion. J. Chem. Inf. Model. 64(22): 8414-8426 (2024) - [c22]Xiaohong Ji, Zhen Wang, Zhifeng Gao, Hang Zheng, Linfeng Zhang, Guolin Ke, Weinan E:
Exploring Molecular Pretraining Model at Scale. NeurIPS 2024 - [c21]Mingze Wang, Jinbo Wang, Haotian He, Zilin Wang, Guanhua Huang, Feiyu Xiong, Zhiyu Li, Weinan E, Lei Wu:
Improving Generalization and Convergence by Enhancing Implicit Regularization. NeurIPS 2024 - [c20]Mingze Wang, Weinan E:
Understanding the Expressive Power and Mechanisms of Transformer for Sequence Modeling. NeurIPS 2024 - [i75]Zhi-Qin John Xu, Junjie Yao, Yuxiao Yi, Liangkai Hang, Weinan E, Yaoyu Zhang, Tianhan Zhang:
Solving multiscale dynamical systems by deep learning. CoRR abs/2401.01220 (2024) - [i74]Zhongwang Zhang, Zhiwei Wang, Junjie Yao, Zhangchen Zhou, Xiaolong Li, Weinan E, Zhi-Qin John Xu:
Anchor function: a type of benchmark functions for studying language models. CoRR abs/2401.08309 (2024) - [i73]Mingze Wang, Weinan E:
Understanding the Expressive Power and Mechanisms of Transformer for Sequence Modeling. CoRR abs/2402.00522 (2024) - [i72]Pinchen Xie, Yunrui Qiu, Weinan E:
Coarse-graining conformational dynamics with multi-dimensional generalized Langevin equation: how, when, and why. CoRR abs/2405.12356 (2024) - [i71]Mingze Wang, Haotian He, Jinbo Wang, Zilin Wang, Guanhua Huang, Feiyu Xiong, Zhiyu Li, Weinan E, Lei Wu:
Improving Generalization and Convergence by Enhancing Implicit Regularization. CoRR abs/2405.20763 (2024) - [i70]Xiaohong Ji, Zhen Wang, Zhifeng Gao, Hang Zheng, Linfeng Zhang, Guolin Ke, Weinan E:
Uni-Mol2: Exploring Molecular Pretraining Model at Scale. CoRR abs/2406.14969 (2024) - [i69]Hongkang Yang, Zehao Lin, Wenjin Wang, Hao Wu, Zhiyu Li, Bo Tang, Wenqiang Wei, Jinbo Wang, Zeyun Tang, Shichao Song, Chenyang Xi, Yu Yu, Kai Chen, Feiyu Xiong, Linpeng Tang, Weinan E:
Memory3: Language Modeling with Explicit Memory. CoRR abs/2407.01178 (2024) - [i68]Boshen Zeng, Sian Chen, Xinxin Liu, Changhong Chen, Bin Deng, Xiaoxu Wang, Zhifeng Gao, Yuzhi Zhang, Weinan E, Linfeng Zhang:
Uni-ELF: A Multi-Level Representation Learning Framework for Electrolyte Formulation Design. CoRR abs/2407.06152 (2024) - [i67]Mingze Wang, Ruoxi Yu, Weinan E, Lei Wu:
How Transformers Implement Induction Heads: Approximation and Optimization Analysis. CoRR abs/2410.11474 (2024) - [i66]Yaorui Shi, Sihang Li, Taiyan Zhang, Xi Fang, Jiankun Wang, Zhiyuan Liu, Guojiang Zhao, Zhengdan Zhu, Zhifeng Gao, Renxin Zhong, Linfeng Zhang, Guolin Ke, Weinan E, Hengxing Cai, Xiang Wang:
Intelligent System for Automated Molecular Patent Infringement Assessment. CoRR abs/2412.07819 (2024) - 2023
- [b1]Gaoyan Ou, Zhanxing Zhu, Bin Dong, Weinan E, Binyang Li, Shumin Shi:
Introduction to Data Science. WorldScientific 2023, ISBN 9789811263897, pp. 1-444 - [j31]Yixiao Chen, Linfeng Zhang, Han Wang, Weinan E:
DeePKS-kit: A package for developing machine learning-based chemically accurate energy and density functional models. Comput. Phys. Commun. 282: 108520 (2023) - [c19]Guanhua Huang, Runxin Xu, Ying Zeng, Jiaze Chen, Zhouwang Yang, Weinan E:
An Iteratively Parallel Generation Method with the Pre-Filling Strategy for Document-level Event Extraction. EMNLP 2023: 10834-10852 - [i65]Zeping Min, Qian Ge, Zhong Li, Weinan E:
AMP: A unified framework boosting low resource automatic speech recognition. CoRR abs/2302.03498 (2023) - [i64]Jingrun Chen, Weinan E, Yixin Luo:
The Random Feature Method for Time-dependent Problems. CoRR abs/2304.06913 (2023) - [i63]Jun Zhang, Xiaohan Lin, Weinan E, Yi Qin Gao:
Machine-Learned Invertible Coarse Graining for Multiscale Molecular Modeling. CoRR abs/2305.01243 (2023) - [i62]Wei Hu, Yue Zhao, Weinan E, Jiequn Han, Jihao Long:
Learning Free Terminal Time Optimal Closed-loop Control of Manipulators. CoRR abs/2311.17749 (2023) - 2022
- [j30]Zhong Li, Jiequn Han, Weinan E, Qianxiao Li:
Approximation and Optimization Theory for Linear Continuous-Time Recurrent Neural Networks. J. Mach. Learn. Res. 23: 42:1-42:85 (2022) - [j29]Dongdong Wang, Yanze Wang, Junhan Chang, Linfeng Zhang, Han Wang, Weinan E:
Efficient sampling of high-dimensional free energy landscapes using adaptive reinforced dynamics. Nat. Comput. Sci. 2(1): 20-29 (2022) - [j28]Weinan E, Yajun Zhou:
A Mathematical Model for Universal Semantics. IEEE Trans. Pattern Anal. Mach. Intell. 44(3): 1124-1132 (2022) - [c18]Yaohua Zang, Jihao Long, Xuanxi Zhang, Wei Hu, Weinan E, Jiequn Han:
A Machine Learning Enhanced Algorithm for the Optimal Landing Problem. MSML 2022: 319-334 - [i61]Zhiwei Wang, Yaoyu Zhang, Yiguang Ju, Weinan E, Zhi-Qin John Xu, Tianhan Zhang:
A deep learning-based model reduction (DeePMR) method for simplifying chemical kinetics. CoRR abs/2201.02025 (2022) - [i60]Tianhan Zhang, Yuxiao Yi, Yifan Xu, Zhi X. Chen, Yaoyu Zhang, Weinan E, Zhi-Qin John Xu:
A multi-scale sampling method for accurate and robust deep neural network to predict combustion chemical kinetics. CoRR abs/2201.03549 (2022) - [i59]Jingrun Chen, Xurong Chi, Weinan E, Zhouwang Yang:
Bridging Traditional and Machine Learning-based Algorithms for Solving PDEs: The Random Feature Method. CoRR abs/2207.13380 (2022) - 2021
- [j27]Denghui Lu, Han Wang, Mohan Chen, Lin Lin, Roberto Car, Weinan E, Weile Jia, Linfeng Zhang:
86 PFLOPS Deep Potential Molecular Dynamics simulation of 100 million atoms with ab initio accuracy. Comput. Phys. Commun. 259: 107624 (2021) - [c17]Zhong Li, Jiequn Han, Weinan E, Qianxiao Li:
On the Curse of Memory in Recurrent Neural Networks: Approximation and Optimization Analysis. ICLR 2021 - [c16]Weinan E, Stephan Wojtowytsch:
Some observations on high-dimensional partial differential equations with Barron data. MSML 2021: 253-269 - [c15]Weinan E, Stephan Wojtowytsch:
On the emergence of simplex symmetry in the final and penultimate layers of neural network classifiers. MSML 2021: 270-290 - [c14]Chao Ma, Lei Wu, Weinan E:
A Qualitative Study of the Dynamic Behavior for Adaptive Gradient Algorithms. MSML 2021: 671-692 - [c13]Hongkang Yang, Weinan E:
Generalization and Memorization: The Bias Potential Model. MSML 2021: 1013-1043 - [i58]Jihao Long, Jiequn Han, Weinan E:
An L2 Analysis of Reinforcement Learning in High Dimensions with Kernel and Neural Network Approximation. CoRR abs/2104.07794 (2021) - [i57]Hongkang Yang, Weinan E:
Generalization Error of GAN from the Discriminator's Perspective. CoRR abs/2107.03633 (2021) - [i56]Jiequn Han, Yucheng Yang, Weinan E:
DeepHAM: A Global Solution Method for Heterogeneous Agent Models with Aggregate Shocks. CoRR abs/2112.14377 (2021) - [i55]Lidong Fang, Pei Ge, Lei Zhang, Huan Lei, Weinan E:
DeePN2: A deep learning-based non-Newtonian hydrodynamic model. CoRR abs/2112.14798 (2021) - 2020
- [j26]Yuzhi Zhang, Haidi Wang, Weijie Chen, Jinzhe Zeng, Linfeng Zhang, Han Wang, Weinan E:
DP-GEN: A concurrent learning platform for the generation of reliable deep learning based potential energy models. Comput. Phys. Commun. 253: 107206 (2020) - [j25]Stephan Wojtowytsch, Weinan E:
Can Shallow Neural Networks Beat the Curse of Dimensionality? A Mean Field Training Perspective. IEEE Trans. Artif. Intell. 1(2): 121-129 (2020) - [c12]Zehao Don, Weinan E, Chao Ma:
A Priori Estimates of the Generalization Error for Autoencoders. ICASSP 2020: 3327-3331 - [c11]Chao Ma, Lei Wu, Weinan E:
The Slow Deterioration of the Generalization Error of the Random Feature Model. MSML 2020: 373-389 - [c10]Pan Zhou, Jiashi Feng, Chao Ma, Caiming Xiong, Steven Chu-Hong Hoi, Weinan E:
Towards Theoretically Understanding Why Sgd Generalizes Better Than Adam in Deep Learning. NeurIPS 2020 - [c9]Weile Jia, Han Wang, Mohan Chen, Denghui Lu, Lin Lin, Roberto Car, Weinan E, Linfeng Zhang:
Pushing the limit of molecular dynamics with ab initio accuracy to 100 million atoms with machine learning. SC 2020: 5 - [i54]Huan Lei, Lei Wu, Weinan E:
Machine learning based non-Newtonian fluid model with molecular fidelity. CoRR abs/2003.03672 (2020) - [i53]Denghui Lu, Han Wang, Mohan Chen, Jiduan Liu, Lin Lin, Roberto Car, Weinan E, Weile Jia, Linfeng Zhang:
86 PFLOPS Deep Potential Molecular Dynamics simulation of 100 million atoms with ab initio accuracy. CoRR abs/2004.11658 (2020) - [i52]Weinan E, Stephan Wojtowytsch:
Kolmogorov Width Decay and Poor Approximators in Machine Learning: Shallow Neural Networks, Random Feature Models and Neural Tangent Kernels. CoRR abs/2005.10807 (2020) - [i51]Stephan Wojtowytsch, Weinan E:
Can Shallow Neural Networks Beat the Curse of Dimensionality? A mean field training perspective. CoRR abs/2005.10815 (2020) - [i50]Weinan E, Jiequn Han, Linfeng Zhang:
Integrating Machine Learning with Physics-Based Modeling. CoRR abs/2006.02619 (2020) - [i49]Weinan E, Stephan Wojtowytsch:
Representation formulas and pointwise properties for Barron functions. CoRR abs/2006.05982 (2020) - [i48]Chao Ma, Lei Wu, Weinan E:
The Quenching-Activation Behavior of the Gradient Descent Dynamics for Two-layer Neural Network Models. CoRR abs/2006.14450 (2020) - [i47]Pinchen Xie, Weinan E:
Coarse-grained spectral projection (CGSP): A scalable and parallelizable deep learning-based approach to quantum unitary dynamics. CoRR abs/2007.09788 (2020) - [i46]Weinan E, Stephan Wojtowytsch:
On the Banach spaces associated with multi-layer ReLU networks: Function representation, approximation theory and gradient descent dynamics. CoRR abs/2007.15623 (2020) - [i45]Yixiao Chen, Linfeng Zhang, Han Wang, Weinan E:
DeePKS: a comprehensive data-driven approach towards chemically accurate density functional theory. CoRR abs/2008.00167 (2020) - [i44]Chao Ma, Lei Wu, Weinan E:
The Slow Deterioration of the Generalization Error of the Random Feature Model. CoRR abs/2008.05621 (2020) - [i43]Weinan E, Jiequn Han, Arnulf Jentzen:
Algorithms for Solving High Dimensional PDEs: From Nonlinear Monte Carlo to Machine Learning. CoRR abs/2008.13333 (2020) - [i42]Haijun Yu, Xinyuan Tian, Weinan E, Qianxiao Li:
OnsagerNet: Learning Stable and Interpretable Dynamics using a Generalized Onsager Principle. CoRR abs/2009.02327 (2020) - [i41]Chao Ma, Lei Wu, Weinan E:
A Qualitative Study of the Dynamic Behavior of Adaptive Gradient Algorithms. CoRR abs/2009.06125 (2020) - [i40]Zhong Li, Jiequn Han, Weinan E, Qianxiao Li:
On the Curse of Memory in Recurrent Neural Networks: Approximation and Optimization Analysis. CoRR abs/2009.07799 (2020) - [i39]Weinan E, Chao Ma, Stephan Wojtowytsch, Lei Wu:
Towards a Mathematical Understanding of Neural Network-Based Machine Learning: what we know and what we don't. CoRR abs/2009.10713 (2020) - [i38]Weinan E, Stephan Wojtowytsch:
A priori estimates for classification problems using neural networks. CoRR abs/2009.13500 (2020) - [i37]Weinan E:
Machine Learning and Computational Mathematics. CoRR abs/2009.14596 (2020) - [i36]Yucheng Yang, Yue Pang, Guanhua Huang, Weinan E:
The Knowledge Graph for Macroeconomic Analysis with Alternative Big Data. CoRR abs/2010.05172 (2020) - [i35]Yucheng Yang, Zhong Zheng, Weinan E:
Interpretable Neural Networks for Panel Data Analysis in Economics. CoRR abs/2010.05311 (2020) - [i34]Pan Zhou, Jiashi Feng, Chao Ma, Caiming Xiong, Steven C. H. Hoi, Weinan E:
Towards Theoretically Understanding Why SGD Generalizes Better Than ADAM in Deep Learning. CoRR abs/2010.05627 (2020) - [i33]Hongkang Yang, Weinan E:
Generalization and Memorization: The Bias Potential Model. CoRR abs/2011.14269 (2020) - [i32]Weinan E, Stephan Wojtowytsch:
Some observations on partial differential equations in Barron and multi-layer spaces. CoRR abs/2012.01484 (2020) - [i31]Weinan E, Stephan Wojtowytsch:
On the emergence of tetrahedral symmetry in the final and penultimate layers of neural network classifiers. CoRR abs/2012.05420 (2020) - [i30]Tianhan Zhang, Yaoyu Zhang, Weinan E, Yiguang Ju:
A deep learning-based ODE solver for chemical kinetics. CoRR abs/2012.12654 (2020)
2010 – 2019
- 2019
- [j24]Jiequn Han, Linfeng Zhang, Weinan E:
Solving many-electron Schrödinger equation using deep neural networks. J. Comput. Phys. 399 (2019) - [j23]Qianxiao Li, Cheng Tai, Weinan E:
Stochastic Modified Equations and Dynamics of Stochastic Gradient Algorithms I: Mathematical Foundations. J. Mach. Learn. Res. 20: 40:1-40:47 (2019) - [j22]Christian Beck, Weinan E, Arnulf Jentzen:
Machine Learning Approximation Algorithms for High-Dimensional Fully Nonlinear Partial Differential Equations and Second-order Backward Stochastic Differential Equations. J. Nonlinear Sci. 29(4): 1563-1619 (2019) - [j21]Weinan E, Martin Hutzenthaler, Arnulf Jentzen, Thomas Kruse:
On Multilevel Picard Numerical Approximations for High-Dimensional Nonlinear Parabolic Partial Differential Equations and High-Dimensional Nonlinear Backward Stochastic Differential Equations. J. Sci. Comput. 79(3): 1534-1571 (2019) - [i29]Weinan E, Chao Ma, Qingcan Wang:
A Priori Estimates of the Population Risk for Residual Networks. CoRR abs/1903.02154 (2019) - [i28]Weinan E, Chao Ma, Lei Wu:
A Comparative Analysis of the Optimization and Generalization Property of Two-layer Neural Network and Random Feature Models Under Gradient Descent Dynamics. CoRR abs/1904.04326 (2019) - [i27]Weinan E, Chao Ma, Qingcan Wang, Lei Wu:
Analysis of the Gradient Descent Algorithm for a Deep Neural Network Model with Skip-connections. CoRR abs/1904.05263 (2019) - [i26]Weinan E, Chao Ma, Lei Wu:
Barron Spaces and the Compositional Function Spaces for Neural Network Models. CoRR abs/1906.08039 (2019) - [i25]Weinan E, Yajun Zhou:
A Mathematical Model for Linguistic Universals. CoRR abs/1907.12293 (2019) - [i24]Weinan E, Chao Ma, Lei Wu:
On the Generalization Properties of Minimum-norm Solutions for Over-parameterized Neural Network Models. CoRR abs/1912.06987 (2019) - [i23]Weinan E, Chao Ma, Lei Wu:
Machine Learning from a Continuous Viewpoint. CoRR abs/1912.12777 (2019) - 2018
- [j20]Han Wang, Linfeng Zhang, Jiequn Han, Weinan E:
DeePMD-kit: A deep learning package for many-body potential energy representation and molecular dynamics. Comput. Phys. Commun. 228: 178-184 (2018) - [c8]Linfeng Zhang, Jiequn Han, Han Wang, Wissam Saidi, Roberto Car, Weinan E:
End-to-end Symmetry Preserving Inter-atomic Potential Energy Model for Finite and Extended Systems. NeurIPS 2018: 4441-4451 - [c7]Lei Wu, Chao Ma, Weinan E:
How SGD Selects the Global Minima in Over-parameterized Learning: A Dynamical Stability Perspective. NeurIPS 2018: 8289-8298 - [i22]Lei Wu, Zhanxing Zhu, Cheng Tai, Weinan E:
Understanding and Enhancing the Transferability of Adversarial Examples. CoRR abs/1802.09707 (2018) - [i21]Weinan E, Qingcan Wang:
Exponential Convergence of the Deep Neural Network Approximation for Analytic Functions. CoRR abs/1807.00297 (2018) - [i20]Weinan E, Jiequn Han, Qianxiao Li:
A Mean-Field Optimal Control Formulation of Deep Learning. CoRR abs/1807.01083 (2018) - [i19]Chao Ma, Jianchun Wang, Weinan E:
Model Reduction with Memory and the Machine Learning of Dynamical Systems. CoRR abs/1808.04258 (2018) - [i18]Linfeng Zhang, Weinan E, Lei Wang:
Monge-Ampère Flow for Generative Modeling. CoRR abs/1809.10188 (2018) - [i17]Weinan E, Chao Ma, Lei Wu:
A Priori Estimates of the Generalization Error for Two-layer Neural Networks. CoRR abs/1810.06397 (2018) - [i16]Linfeng Zhang, De-Ye Lin, Han Wang, Roberto Car, Weinan E:
Active Learning of Uniformly Accurate Inter-atomic Potentials for Materials Simulation. CoRR abs/1810.11890 (2018) - [i15]Qianxiao Li, Cheng Tai, Weinan E:
Stochastic Modified Equations and Dynamics of Stochastic Gradient Algorithms I: Mathematical Foundations. CoRR abs/1811.01558 (2018) - 2017
- [j19]Qianxiao Li, Long Chen, Cheng Tai, Weinan E:
Maximum Principle Based Algorithms for Deep Learning. J. Mach. Learn. Res. 18: 165:1-165:29 (2017) - [c6]Qianxiao Li, Cheng Tai, Weinan E:
Stochastic Modified Equations and Adaptive Stochastic Gradient Algorithms. ICML 2017: 2101-2110 - [c5]Rui Yan, Dongyan Zhao, Weinan E:
Joint Learning of Response Ranking and Next Utterance Suggestion in Human-Computer Conversation System. SIGIR 2017: 685-694 - [i14]Weinan E, Jiequn Han, Arnulf Jentzen:
Deep learning-based numerical methods for high-dimensional parabolic partial differential equations and backward stochastic differential equations. CoRR abs/1706.04702 (2017) - [i13]Lei Wu, Zhanxing Zhu, Weinan E:
Towards Understanding Generalization of Deep Learning: Perspective of Loss Landscapes. CoRR abs/1706.10239 (2017) - [i12]Jiequn Han, Arnulf Jentzen, Weinan E:
Overcoming the curse of dimensionality: Solving high-dimensional partial differential equations using deep learning. CoRR abs/1707.02568 (2017) - [i11]Linfeng Zhang, Jiequn Han, Han Wang, Roberto Car, Weinan E:
Deep Potential Molecular Dynamics: a scalable model with the accuracy of quantum mechanics. CoRR abs/1707.09571 (2017) - [i10]Christian Beck, Weinan E, Arnulf Jentzen:
Machine learning approximation algorithms for high-dimensional fully nonlinear partial differential equations and second-order backward stochastic differential equations. CoRR abs/1709.05963 (2017) - [i9]Weinan E, Bing Yu:
The Deep Ritz method: A deep learning-based numerical algorithm for solving variational problems. CoRR abs/1710.00211 (2017) - [i8]Qianxiao Li, Long Chen, Cheng Tai, Weinan E:
Maximum Principle Based Algorithms for Deep Learning. CoRR abs/1710.09513 (2017) - [i7]Linfeng Zhang, Han Wang, Weinan E:
Reinforced dynamics for enhanced sampling in large atomic and molecular systems. I. Basic Methodology. CoRR abs/1712.03461 (2017) - [i6]Han Wang, Linfeng Zhang, Jiequn Han, Weinan E:
DeePMD-kit: A deep learning package for many-body potential energy representation and molecular dynamics. CoRR abs/1712.03641 (2017) - 2016
- [j18]Cheng Tai, Weinan E:
Multiscale Adaptive Representation of Signals: I. The Basic Framework. J. Mach. Learn. Res. 17: 140:1-140:38 (2016) - [c4]Chu Wang, Qianxiao Li, Weinan E, Bernard Chazelle:
Noisy Hegselmann-Krause systems: Phase transition and the 2R-conjecture. CDC 2016: 2632-2637 - [c3]Cheng Tai, Tong Xiao, Xiaogang Wang, Weinan E:
Convolutional neural networks with low-rank regularization. ICLR (Poster) 2016 - [i5]Jiequn Han, Weinan E:
Deep Learning Approximation for Stochastic Control Problems. CoRR abs/1611.07422 (2016) - 2015
- [i4]Cheng Tai, Weinan E:
Multiscale Adaptive Representation of Signals: I. The Basic Framework. CoRR abs/1507.04835 (2015) - [i3]Chu Wang, Yingfei Wang, Weinan E, Robert E. Schapire:
Functional Frank-Wolfe Boosting for General Loss Functions. CoRR abs/1510.02558 (2015) - [i2]Qianxiao Li, Cheng Tai, Weinan E:
Dynamics of Stochastic Gradient Algorithms. CoRR abs/1511.06251 (2015) - 2014
- [c2]Haoshu Tian, Weinan E:
Fire sale in financial networks. CISS 2014: 1-5 - 2013
- [j17]Lin Lin, Sihong Shao, Weinan E:
Efficient iterative method for solving the Dirac-Kohn-Sham density functional theory. J. Comput. Phys. 245: 205-217 (2013) - 2012
- [j16]Assyr Abdulle, Weinan E, Björn Engquist, Eric Vanden-Eijnden:
The heterogeneous multiscale method. Acta Numer. 21: 1-87 (2012) - [j15]Lin Lin, Jianfeng Lu, Lexing Ying, Weinan E:
Adaptive local basis set for Kohn-Sham density functional theory in a discontinuous Galerkin framework I: Total energy calculation. J. Comput. Phys. 231(4): 2140-2154 (2012) - [j14]Lin Lin, Jianfeng Lu, Lexing Ying, Weinan E:
Optimized local basis set for Kohn-Sham density functional theory. J. Comput. Phys. 231(13): 4515-4529 (2012) - [i1]Weinan E, Jianfeng Lu, Yuan Yao:
The Landscape of Complex Networks. CoRR abs/1204.6376 (2012) - 2011
- [j13]Weinan E, Jianfeng Lu:
Multiscale modeling. Scholarpedia 6(10): 11527 (2011) - [j12]Lin Lin, Chao Yang, Jianfeng Lu, Lexing Ying, Weinan E:
A Fast Parallel Algorithm for Selected Inversion of Structured Sparse Matrices with Application to 2D Electronic Structure Calculations. SIAM J. Sci. Comput. 33(3): 1329-1351 (2011) - [j11]Lin Lin, Chao Yang, Juan C. Meza, Jianfeng Lu, Lexing Ying, Weinan E:
SelInv - An Algorithm for Selected Inversion of a Sparse Symmetric Matrix. ACM Trans. Math. Softw. 37(4): 40:1-40:19 (2011) - [c1]Jingchen Liu, Rohit Patra, Xiang Zhou, Weinan E:
Failure of random materials: a large deviation and computational study. WSC 2011: 3784-3794 - 2010
- [j10]Ling Lin, Xiuyuan Cheng, Weinan E, An-Chang Shi, Pingwen Zhang:
A numerical method for the study of nucleation of ordered phases. J. Comput. Phys. 229(5): 1797-1809 (2010) - [j9]Xiantao Li, Jerry Zhijian Yang, Weinan E:
A multiscale coupling method for the modeling of dynamics of solids with application to brittle cracks. J. Comput. Phys. 229(10): 3970-3987 (2010)
2000 – 2009
- 2009
- [j8]Weinan E, Weiqing Ren, Eric Vanden-Eijnden:
A general strategy for designing seamless multiscale methods. J. Comput. Phys. 228(15): 5437-5453 (2009) - 2007
- [j7]Weinan E, Di Liu, Eric Vanden-Eijnden:
Nested stochastic simulation algorithms for chemical kinetic systems with multiple time scales. J. Comput. Phys. 221(1): 158-180 (2007) - [j6]Xingye Yue, Weinan E:
The local microscale problem in the multiscale modeling of strongly heterogeneous media: Effects of boundary conditions and cell size. J. Comput. Phys. 222(2): 556-572 (2007) - [j5]Shanqin Chen, Weinan E, Yunxian Liu, Chi-Wang Shu:
A discontinuous Galerkin implementation of a domain decomposition method for kinetic-hydrodynamic coupling multiscale problems in gas dynamics and device simulations. J. Comput. Phys. 225(2): 1314-1330 (2007) - 2005
- [j4]Shanqin Chen, Weinan E, Chi-Wang Shu:
The Heterogeneous Multiscale Method Based on the Discontinuous Galerkin Method for Hyperbolic and Parabolic Problems. Multiscale Model. Simul. 3(4): 871-894 (2005) - 2002
- [j3]Weinan E, Jian-Guo Liu:
Projection method III: Spatial discretization on the staggered grid. Math. Comput. 71(237): 27-47 (2002) - 2001
- [j2]Jian-Guo Liu, Weinan E:
Simple finite element method in vorticity formulation for incompressible flows. Math. Comput. 70(234): 579-593 (2001) - 2000
- [j1]Weinan E, Xiao-Ping Wang:
Numerical Methods for the Landau-Lifshitz Equation. SIAM J. Numer. Anal. 38(5): 1647-1665 (2000)
Coauthor Index
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