Weinan E - RankMe

162 papers A* 12A 1C 1Misc 3Journal 136Unranked 8

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	DIA-CLIP: a universal representation learning framework for zero-shot DIA proteomics. CoRR Yucheng Liao, Han Wen, Weinan E, Weijie Zhang
2026	J	`jnl`	DataFlex: A Unified Framework for Data-Centric Dynamic Training of Large Language Models. CoRR 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
2026	J	`jnl`	From Human Labels to Literature: Semi-Supervised Learning of NMR Chemical Shifts at Scale. CoRR Yongqi Jin, Yecheng Wang, Junjie Wang, Rong Zhu, Guolin Ke, Weinan E
2026	J	`jnl`	Generative Teaching via Code. CoRR Yuheng Wang, Runde Yang, Lin Wu, Jie Zhang, Jingru Fan, Ruoyu Fu, Tianle Zhou, Huatao Li, Siheng Chen, Weinan E, Chen Qian
2026	J	`jnl`	Innovator-VL: A Multimodal Large Language Model for Scientific Discovery. CoRR 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
2026	J	`jnl`	Scaling Machine Learning Interatomic Potentials with Mixtures of Experts. CoRR Yuzhi Liu, Duo Zhang, Anyang Peng, Weinan E, Linfeng Zhang, Han Wang
2026	J	`jnl`	Toward Ultra-Long-Horizon Agentic Science: Cognitive Accumulation for Machine Learning Engineering. CoRR 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
2026	J	`jnl`	Towards Next-Generation LLM Training: From the Data-Centric Perspective. CoRR Hao Liang, Zhengyang Zhao, Zhaoyang Han, Meiyi Qiang, Xiaochen Ma, Bohan Zeng, Qifeng Cai, Zhiyu Li, Linpeng Tang, Weinan E, Wentao Zhang
2025	J	`jnl`	A brief review of the Deep BSDE method for solving high-dimensional partial differential equations. CoRR Jiequn Han, Arnulf Jentzen, Weinan E
2025	J	`jnl`	Bohrium + SciMaster: Building the Infrastructure and Ecosystem for Agentic Science at Scale. CoRR 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, Tianhan Zhang, Wenchang Zhang, Yuzhi Zhang, Zezhong Zhang, Hang Zheng, Hui Zhou, Tong Zhu, Xinyu Zhu, Qingguo Zhou, Weinan E
2025	J	`jnl`	DataFlow: An LLM-Driven Framework for Unified Data Preparation and Workflow Automation in the Era of Data-Centric AI. CoRR 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
2025	J	`jnl`	GradPower: Powering Gradients for Faster Language Model Pre-Training. CoRR Mingze Wang, Jinbo Wang, Jiaqi Zhang, Wei Wang, Peng Pei, Xunliang Cai, Weinan E, Lei Wu
2025	J	`jnl`	Inverse Knowledge Search over Verifiable Reasoning: Synthesizing a Scientific Encyclopedia from a Long Chains-of-Thought Knowledge Base. CoRR 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, Zhiyuan Yao, Kun Chen
2025	C	`conf`	Learning Free Terminal Time Optimal Closed-loop Control of Manipulators. ACC Wei Hu, Yue Zhao, Weinan E, Jiequn Han, Jihao Long
2025	J	`jnl`	ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning. CoRR Zexi Liu, Yuzhu Cai, Xinyu Zhu, Yujie Zheng, Runkun Chen, Ying Wen, Yanfeng Wang, Weinan E, Siheng Chen
2025	J	`jnl`	NMR-Solver: Automated Structure Elucidation via Large-Scale Spectral Matching and Physics-Guided Fragment Optimization. CoRR Yong-Jin Liu, Junjie Wang, Fanjie Xu, Xiaohong Ji, Zhifeng Gao, Linfeng Zhang, Guolin Ke, Rong Zhu, Weinan E
2025	J	`jnl`	On the Expressive Power of Mixture-of-Experts for Structured Complex Tasks. CoRR Mingze Wang, Weinan E
2025	—	`conf`	PaSa: An LLM Agent for Comprehensive Academic Paper Search. ACL (1) Yichen He, Guanhua Huang, Peiyuan Feng, Yuan Lin, Yuchen Zhang, Hang Li, Weinan E
2025	J	`jnl`	PaSa: An LLM Agent for Comprehensive Academic Paper Search. CoRR Yichen He, Guanhua Huang, Peiyuan Feng, Yuan Lin, Yuchen Zhang, Hang Li, Weinan E
2025	J	`jnl`	PhysMaster: Building an Autonomous AI Physicist for Theoretical and Computational Physics Research. CoRR 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
2025	J	`jnl`	RARE: Retrieval-Augmented Reasoning Modeling. CoRR Zhengren Wang, Jiayang Yu, Dongsheng Ma, Zhe Chen, Yu Wang, Zhiyu Li, Feiyu Xiong, Yanfeng Wang, Weinan E, Linpeng Tang, Wentao Zhang
2025	J	`jnl`	Scalable Complexity Control Facilitates Reasoning Ability of LLMs. CoRR 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
2025	J	`jnl`	SciMaster: Towards General-Purpose Scientific AI Agents, Part I. X-Master as Foundation: Can We Lead on Humanity's Last Exam? CoRR Jingyi Chai, Shuo Tang, Rui Ye, Yuwen Du, Xinyu Zhu, Mengcheng Zhou, Yanfeng Wang, Weinan E, Yuzhi Zhang, Linfeng Zhang, Siheng Chen
2025	J	`jnl`	Solving multiscale dynamical systems by deep learning. Comput. Phys. Commun. Junjie Yao, Yuxiao Yi, Liangkai Hang, Weinan E, Weizong Wang, Yaoyu Zhang, Tianhan Zhang, Zhi-Qin John Xu
2025	J	`jnl`	Solving optimal control problems of rigid-body dynamics with collisions using the hybrid minimum principle. Commun. Nonlinear Sci. Numer. Simul. Wei Hu, Jihao Long, Yaohua Zang, Weinan E, Jiequn Han
2025	J	`jnl`	Strategic priorities for transformative progress in advancing biology with proteomics and artificial intelligence. CoRR 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
2025	J	`jnl`	SynBridge: Bridging Reaction States via Discrete Flow for Bidirectional Reaction Prediction. CoRR Haitao Lin, Junjie Wang, Zhifeng Gao, Xiaohong Ji, Rong Zhu, Linfeng Zhang, Guolin Ke, Weinan E
2025	A*	`conf`	The Sharpness Disparity Principle in Transformers for Accelerating Language Model Pre-Training. ICML Jinbo Wang, Mingze Wang, Zhanpeng Zhou, Junchi Yan, Weinan E, Lei Wu
2025	J	`jnl`	The Sharpness Disparity Principle in Transformers for Accelerating Language Model Pre-Training. CoRR Jinbo Wang, Mingze Wang, Zhanpeng Zhou, Junchi Yan, Weinan E, Lei Wu
2025	J	`jnl`	Toward a unified benchmark and framework for deep learning-based prediction of nuclear magnetic resonance chemical shifts. Nat. Comput. Sci. Fanjie Xu, Wentao Guo, Feng Wang, Lin Yao, Hongshuai Wang, Fujie Tang, Zhifeng Gao, Linfeng Zhang, Weinan E, Zhong-Qun Tian, Jun Cheng
2025	J	`jnl`	Uni-3DAR: Unified 3D Generation and Understanding via Autoregression on Compressed Spatial Tokens. CoRR Shuqi Lu, Haowei Lin, Lin Yao, Zhifeng Gao, Xiaohong Ji, Weinan E, Linfeng Zhang, Guolin Ke
2025	J	`jnl`	pUniFind: a unified large pre-trained deep learning model pushing the limit of mass spectra interpretation. CoRR 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
2024	J	`jnl`	Accurate Conformation Sampling via Protein Structural Diffusion. J. Chem. Inf. Model. Jiahao Fan, Ziyao Li, Eric Alcaide, Guolin Ke, Huaqing Huang, Weinan E
2024	J	`jnl`	Anchor function: a type of benchmark functions for studying language models. CoRR Zhongwang Zhang, Zhiwei Wang, Junjie Yao, Zhangchen Zhou, Xiaolong Li, Weinan E, Zhi-Qin John Xu
2024	J	`jnl`	Coarse-graining conformational dynamics with multi-dimensional generalized Langevin equation: how, when, and why. CoRR Pinchen Xie, Yunrui Qiu, Weinan E
2024	A*	`conf`	Exploring Molecular Pretraining Model at Scale. NeurIPS Xiaohong Ji, Zhen Wang, Zhifeng Gao, Hang Zheng, Linfeng Zhang, Guolin Ke, Weinan E
2024	J	`jnl`	How Transformers Implement Induction Heads: Approximation and Optimization Analysis. CoRR Mingze Wang, Ruoxi Yu, Weinan E, Lei Wu
2024	A*	`conf`	Improving Generalization and Convergence by Enhancing Implicit Regularization. NeurIPS Mingze Wang, Jinbo Wang, Haotian He, Zilin Wang, Guanhua Huang, Feiyu Xiong, Zhiyu Li, Weinan E, Lei Wu
2024	J	`jnl`	Improving Generalization and Convergence by Enhancing Implicit Regularization. CoRR Mingze Wang, Haotian He, Jinbo Wang, Zilin Wang, Guanhua Huang, Feiyu Xiong, Zhiyu Li, Weinan E, Lei Wu
2024	J	`jnl`	Intelligent System for Automated Molecular Patent Infringement Assessment. CoRR 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
2024	J	`jnl`	Memory CoRR 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
2024	J	`jnl`	Solving multiscale dynamical systems by deep learning. CoRR Zhi-Qin John Xu, Junjie Yao, Yuxiao Yi, Liangkai Hang, Weinan E, Yaoyu Zhang, Tianhan Zhang
2024	A*	`conf`	Understanding the Expressive Power and Mechanisms of Transformer for Sequence Modeling. NeurIPS Mingze Wang, Weinan E
2024	J	`jnl`	Understanding the Expressive Power and Mechanisms of Transformer for Sequence Modeling. CoRR Mingze Wang, Weinan E
2024	J	`jnl`	Uni-ELF: A Multi-Level Representation Learning Framework for Electrolyte Formulation Design. CoRR Boshen Zeng, Sian Chen, Xinxin Liu, Changhong Chen, Bin Deng, Xiaoxu Wang, Zhifeng Gao, Yuzhi Zhang, Weinan E, Linfeng Zhang
2024	J	`jnl`	Uni-Mol2: Exploring Molecular Pretraining Model at Scale. CoRR Xiaohong Ji, Zhen Wang, Zhifeng Gao, Hang Zheng, Linfeng Zhang, Guolin Ke, Weinan E
2023	J	`jnl`	AMP: A unified framework boosting low resource automatic speech recognition. CoRR Zeping Min, Qian Ge, Zhong Li, Weinan E
2023	A*	`conf`	An Iteratively Parallel Generation Method with the Pre-Filling Strategy for Document-level Event Extraction. EMNLP Guanhua Huang, Runxin Xu, Ying Zeng, Jiaze Chen, Zhouwang Yang, Weinan E
2023	J	`jnl`	DeePKS-kit: A package for developing machine learning-based chemically accurate energy and density functional models. Comput. Phys. Commun. Yixiao Chen, Linfeng Zhang, Han Wang, Weinan E
2023	—	`book`	Introduction to Data Science Gaoyan Ou, Zhanxing Zhu, Bin Dong, Weinan E, Binyang Li, Shumin Shi
2023	J	`jnl`	Learning Free Terminal Time Optimal Closed-loop Control of Manipulators. CoRR Wei Hu, Yue Zhao, Weinan E, Jiequn Han, Jihao Long
2023	J	`jnl`	Machine-Learned Invertible Coarse Graining for Multiscale Molecular Modeling. CoRR Jun Zhang, Xiaohan Lin, Weinan E, Yi Qin Gao
2023	J	`jnl`	The Random Feature Method for Time-dependent Problems. CoRR Jingrun Chen, Weinan E, Yixin Luo
2022	—	`conf`	A Machine Learning Enhanced Algorithm for the Optimal Landing Problem. MSML Yaohua Zang, Jihao Long, Xuanxi Zhang, Wei Hu, Weinan E, Jiequn Han
2022	J	`jnl`	A Mathematical Model for Universal Semantics. IEEE Trans. Pattern Anal. Mach. Intell. Weinan E, Yajun Zhou
2022	J	`jnl`	A deep learning-based model reduction (DeePMR) method for simplifying chemical kinetics. CoRR Zhiwei Wang, Yaoyu Zhang, Yiguang Ju, Weinan E, Zhi-Qin John Xu, Tianhan Zhang
2022	J	`jnl`	A multi-scale sampling method for accurate and robust deep neural network to predict combustion chemical kinetics. CoRR Tianhan Zhang, Yuxiao Yi, Yifan Xu, Zhi X. Chen, Yaoyu Zhang, Weinan E, Zhi-Qin John Xu
2022	J	`jnl`	Approximation and Optimization Theory for Linear Continuous-Time Recurrent Neural Networks. J. Mach. Learn. Res. Zhong Li, Jiequn Han, Weinan E, Qianxiao Li
2022	J	`jnl`	Bridging Traditional and Machine Learning-based Algorithms for Solving PDEs: The Random Feature Method. CoRR Jingrun Chen, Xurong Chi, Weinan E, Zhouwang Yang
2022	J	`jnl`	Efficient sampling of high-dimensional free energy landscapes using adaptive reinforced dynamics. Nat. Comput. Sci. Dongdong Wang, Yanze Wang, Junhan Chang, Linfeng Zhang, Han Wang, Weinan E
2021	J	`jnl`	86 PFLOPS Deep Potential Molecular Dynamics simulation of 100 million atoms with Comput. Phys. Commun. Denghui Lu, Han Wang, Mohan Chen, Lin Lin, Roberto Car, Weinan E, Weile Jia, Linfeng Zhang
2021	—	`conf`	A Qualitative Study of the Dynamic Behavior for Adaptive Gradient Algorithms. MSML Chao Ma, Lei Wu, Weinan E
2021	J	`jnl`	An L CoRR Jihao Long, Jiequn Han, Weinan E
2021	J	`jnl`	DeePN CoRR Lidong Fang, Pei Ge, Lei Zhang, Huan Lei, Weinan E
2021	J	`jnl`	DeepHAM: A Global Solution Method for Heterogeneous Agent Models with Aggregate Shocks. CoRR Jiequn Han, Yucheng Yang, Weinan E
2021	J	`jnl`	Generalization Error of GAN from the Discriminator's Perspective. CoRR Hongkang Yang, Weinan E
2021	—	`conf`	Generalization and Memorization: The Bias Potential Model. MSML Hongkang Yang, Weinan E
2021	A*	`conf`	On the Curse of Memory in Recurrent Neural Networks: Approximation and Optimization Analysis. ICLR Zhong Li, Jiequn Han, Weinan E, Qianxiao Li
2021	—	`conf`	On the emergence of simplex symmetry in the final and penultimate layers of neural network classifiers. MSML Weinan E, Stephan Wojtowytsch
2021	—	`conf`	Some observations on high-dimensional partial differential equations with Barron data. MSML Weinan E, Stephan Wojtowytsch
2020	J	`jnl`	86 PFLOPS Deep Potential Molecular Dynamics simulation of 100 million atoms with ab initio accuracy. CoRR Denghui Lu, Han Wang, Mohan Chen, Jiduan Liu, Lin Lin, Roberto Car, Weinan E, Weile Jia, Linfeng Zhang
2020	Misc	`conf`	A Priori Estimates of the Generalization Error for Autoencoders. ICASSP Zehao Don, Weinan E, Chao Ma
2020	J	`jnl`	A Qualitative Study of the Dynamic Behavior of Adaptive Gradient Algorithms. CoRR Chao Ma, Lei Wu, Weinan E
2020	J	`jnl`	A deep learning-based ODE solver for chemical kinetics. CoRR Tianhan Zhang, Yaoyu Zhang, Weinan E, Yiguang Ju
2020	J	`jnl`	A priori estimates for classification problems using neural networks. CoRR Weinan E, Stephan Wojtowytsch
2020	J	`jnl`	Algorithms for Solving High Dimensional PDEs: From Nonlinear Monte Carlo to Machine Learning. CoRR Weinan E, Jiequn Han, Arnulf Jentzen
2020	J	`jnl`	Can Shallow Neural Networks Beat the Curse of Dimensionality? A Mean Field Training Perspective. IEEE Trans. Artif. Intell. Stephan Wojtowytsch, Weinan E
2020	J	`jnl`	Can Shallow Neural Networks Beat the Curse of Dimensionality? A mean field training perspective. CoRR Stephan Wojtowytsch, Weinan E
2020	J	`jnl`	Coarse-grained spectral projection (CGSP): A scalable and parallelizable deep learning-based approach to quantum unitary dynamics. CoRR Pinchen Xie, Weinan E
2020	J	`jnl`	DP-GEN: A concurrent learning platform for the generation of reliable deep learning based potential energy models. Comput. Phys. Commun. Yuzhi Zhang, Haidi Wang, Weijie Chen, Jinzhe Zeng, Linfeng Zhang, Han Wang, Weinan E
2020	J	`jnl`	DeePKS: a comprehensive data-driven approach towards chemically accurate density functional theory. CoRR Yixiao Chen, Linfeng Zhang, Han Wang, Weinan E
2020	J	`jnl`	Generalization and Memorization: The Bias Potential Model. CoRR Hongkang Yang, Weinan E
2020	J	`jnl`	Integrating Machine Learning with Physics-Based Modeling. CoRR Weinan E, Jiequn Han, Linfeng Zhang
2020	J	`jnl`	Interpretable Neural Networks for Panel Data Analysis in Economics. CoRR Yucheng Yang, Zhong Zheng, Weinan E
2020	J	`jnl`	Kolmogorov Width Decay and Poor Approximators in Machine Learning: Shallow Neural Networks, Random Feature Models and Neural Tangent Kernels. CoRR Weinan E, Stephan Wojtowytsch
2020	J	`jnl`	Machine Learning and Computational Mathematics. CoRR Weinan E
2020	J	`jnl`	Machine learning based non-Newtonian fluid model with molecular fidelity. CoRR Huan Lei, Lei Wu, Weinan E
2020	J	`jnl`	On the Banach spaces associated with multi-layer ReLU networks: Function representation, approximation theory and gradient descent dynamics. CoRR Weinan E, Stephan Wojtowytsch
2020	J	`jnl`	On the Curse of Memory in Recurrent Neural Networks: Approximation and Optimization Analysis. CoRR Zhong Li, Jiequn Han, Weinan E, Qianxiao Li
2020	J	`jnl`	On the emergence of tetrahedral symmetry in the final and penultimate layers of neural network classifiers. CoRR Weinan E, Stephan Wojtowytsch
2020	J	`jnl`	OnsagerNet: Learning Stable and Interpretable Dynamics using a Generalized Onsager Principle. CoRR Haijun Yu, Xinyuan Tian, Weinan E, Qianxiao Li
2020	A	`conf`	Pushing the limit of molecular dynamics with SC Weile Jia, Han Wang, Mohan Chen, Denghui Lu, Lin Lin, Roberto Car, Weinan E, Linfeng Zhang
2020	J	`jnl`	Representation formulas and pointwise properties for Barron functions. CoRR Weinan E, Stephan Wojtowytsch
2020	J	`jnl`	Some observations on partial differential equations in Barron and multi-layer spaces. CoRR Weinan E, Stephan Wojtowytsch
2020	J	`jnl`	The Knowledge Graph for Macroeconomic Analysis with Alternative Big Data. CoRR Yucheng Yang, Yue Pang, Guanhua Huang, Weinan E
2020	J	`jnl`	The Quenching-Activation Behavior of the Gradient Descent Dynamics for Two-layer Neural Network Models. CoRR Chao Ma, Lei Wu, Weinan E
2020	—	`conf`	The Slow Deterioration of the Generalization Error of the Random Feature Model. MSML Chao Ma, Lei Wu, Weinan E
2020	J	`jnl`	The Slow Deterioration of the Generalization Error of the Random Feature Model. CoRR Chao Ma, Lei Wu, Weinan E
2020	J	`jnl`	Towards Theoretically Understanding Why SGD Generalizes Better Than ADAM in Deep Learning. CoRR Pan Zhou, Jiashi Feng, Chao Ma, Caiming Xiong, Steven C. H. Hoi, Weinan E
2020	A*	`conf`	Towards Theoretically Understanding Why Sgd Generalizes Better Than Adam in Deep Learning. NeurIPS Pan Zhou, Jiashi Feng, Chao Ma, Caiming Xiong, Steven Chu-Hong Hoi, Weinan E
2020	J	`jnl`	Towards a Mathematical Understanding of Neural Network-Based Machine Learning: what we know and what we don't. CoRR Weinan E, Chao Ma, Stephan Wojtowytsch, Lei Wu
2019	J	`jnl`	A Comparative Analysis of the Optimization and Generalization Property of Two-layer Neural Network and Random Feature Models Under Gradient Descent Dynamics. CoRR Weinan E, Chao Ma, Lei Wu
2019	J	`jnl`	A Mathematical Model for Linguistic Universals. CoRR Weinan E, Yajun Zhou
2019	J	`jnl`	A Priori Estimates of the Population Risk for Residual Networks. CoRR Weinan E, Chao Ma, Qingcan Wang
2019	J	`jnl`	Analysis of the Gradient Descent Algorithm for a Deep Neural Network Model with Skip-connections. CoRR Weinan E, Chao Ma, Qingcan Wang, Lei Wu
2019	J	`jnl`	Barron Spaces and the Compositional Function Spaces for Neural Network Models. CoRR Weinan E, Chao Ma, Lei Wu
2019	J	`jnl`	Machine Learning Approximation Algorithms for High-Dimensional Fully Nonlinear Partial Differential Equations and Second-order Backward Stochastic Differential Equations. J. Nonlinear Sci. Christian Beck, Weinan E, Arnulf Jentzen
2019	J	`jnl`	Machine Learning from a Continuous Viewpoint. CoRR Weinan E, Chao Ma, Lei Wu
2019	J	`jnl`	On Multilevel Picard Numerical Approximations for High-Dimensional Nonlinear Parabolic Partial Differential Equations and High-Dimensional Nonlinear Backward Stochastic Differential Equations. J. Sci. Comput. Weinan E, Martin Hutzenthaler, Arnulf Jentzen, Thomas Kruse
2019	J	`jnl`	On the Generalization Properties of Minimum-norm Solutions for Over-parameterized Neural Network Models. CoRR Weinan E, Chao Ma, Lei Wu
2019	J	`jnl`	Solving many-electron Schrödinger equation using deep neural networks. J. Comput. Phys. Jiequn Han, Linfeng Zhang, Weinan E
2019	J	`jnl`	Stochastic Modified Equations and Dynamics of Stochastic Gradient Algorithms I: Mathematical Foundations. J. Mach. Learn. Res. Qianxiao Li, Cheng Tai, Weinan E
2018	J	`jnl`	A Mean-Field Optimal Control Formulation of Deep Learning. CoRR Weinan E, Jiequn Han, Qianxiao Li
2018	J	`jnl`	A Priori Estimates of the Generalization Error for Two-layer Neural Networks. CoRR Weinan E, Chao Ma, Lei Wu
2018	J	`jnl`	Active Learning of Uniformly Accurate Inter-atomic Potentials for Materials Simulation. CoRR Linfeng Zhang, De-Ye Lin, Han Wang, Roberto Car, Weinan E
2018	J	`jnl`	DeePMD-kit: A deep learning package for many-body potential energy representation and molecular dynamics. Comput. Phys. Commun. Han Wang, Linfeng Zhang, Jiequn Han, Weinan E
2018	A*	`conf`	End-to-end Symmetry Preserving Inter-atomic Potential Energy Model for Finite and Extended Systems. NeurIPS Linfeng Zhang, Jiequn Han, Han Wang, Wissam Saidi, Roberto Car, Weinan E
2018	J	`jnl`	Exponential Convergence of the Deep Neural Network Approximation for Analytic Functions. CoRR Weinan E, Qingcan Wang
2018	A*	`conf`	How SGD Selects the Global Minima in Over-parameterized Learning: A Dynamical Stability Perspective. NeurIPS Lei Wu, Chao Ma, Weinan E
2018	J	`jnl`	Model Reduction with Memory and the Machine Learning of Dynamical Systems. CoRR Chao Ma, Jianchun Wang, Weinan E
2018	J	`jnl`	Monge-Ampère Flow for Generative Modeling. CoRR Linfeng Zhang, Weinan E, Lei Wang
2018	J	`jnl`	Stochastic Modified Equations and Dynamics of Stochastic Gradient Algorithms I: Mathematical Foundations. CoRR Qianxiao Li, Cheng Tai, Weinan E
2018	J	`jnl`	Understanding and Enhancing the Transferability of Adversarial Examples. CoRR Lei Wu, Zhanxing Zhu, Cheng Tai, Weinan E
2017	J	`jnl`	DeePMD-kit: A deep learning package for many-body potential energy representation and molecular dynamics. CoRR Han Wang, Linfeng Zhang, Jiequn Han, Weinan E
2017	J	`jnl`	Deep Potential Molecular Dynamics: a scalable model with the accuracy of quantum mechanics. CoRR Linfeng Zhang, Jiequn Han, Han Wang, Roberto Car, Weinan E
2017	J	`jnl`	Deep learning-based numerical methods for high-dimensional parabolic partial differential equations and backward stochastic differential equations. CoRR Weinan E, Jiequn Han, Arnulf Jentzen
2017	A*	`conf`	Joint Learning of Response Ranking and Next Utterance Suggestion in Human-Computer Conversation System. SIGIR Rui Yan, Dongyan Zhao, Weinan E
2017	J	`jnl`	Machine learning approximation algorithms for high-dimensional fully nonlinear partial differential equations and second-order backward stochastic differential equations. CoRR Christian Beck, Weinan E, Arnulf Jentzen
2017	J	`jnl`	Maximum Principle Based Algorithms for Deep Learning. CoRR Qianxiao Li, Long Chen, Cheng Tai, Weinan E
2017	J	`jnl`	Maximum Principle Based Algorithms for Deep Learning. J. Mach. Learn. Res. Qianxiao Li, Long Chen, Cheng Tai, Weinan E
2017	J	`jnl`	Overcoming the curse of dimensionality: Solving high-dimensional partial differential equations using deep learning. CoRR Jiequn Han, Arnulf Jentzen, Weinan E
2017	J	`jnl`	Reinforced dynamics for enhanced sampling in large atomic and molecular systems. I. Basic Methodology. CoRR Linfeng Zhang, Han Wang, Weinan E
2017	A*	`conf`	Stochastic Modified Equations and Adaptive Stochastic Gradient Algorithms. ICML Qianxiao Li, Cheng Tai, Weinan E
2017	J	`jnl`	The Deep Ritz method: A deep learning-based numerical algorithm for solving variational problems. CoRR Weinan E, Bing Yu
2017	J	`jnl`	Towards Understanding Generalization of Deep Learning: Perspective of Loss Landscapes. CoRR Lei Wu, Zhanxing Zhu, Weinan E
2016	A*	`conf`	Convolutional neural networks with low-rank regularization. ICLR (Poster) Cheng Tai, Tong Xiao, Xiaogang Wang, Weinan E
2016	J	`jnl`	Deep Learning Approximation for Stochastic Control Problems. CoRR Jiequn Han, Weinan E
2016	J	`jnl`	Multiscale Adaptive Representation of Signals: I. The Basic Framework. J. Mach. Learn. Res. Cheng Tai, Weinan E
2016	—	`conf`	Noisy Hegselmann-Krause systems: Phase transition and the 2R-conjecture. CDC Chu Wang, Qianxiao Li, Weinan E, Bernard Chazelle
2015	J	`jnl`	Dynamics of Stochastic Gradient Algorithms. CoRR Qianxiao Li, Cheng Tai, Weinan E
2015	J	`jnl`	Functional Frank-Wolfe Boosting for General Loss Functions. CoRR Chu Wang, Yingfei Wang, Weinan E, Robert E. Schapire
2015	J	`jnl`	Multiscale Adaptive Representation of Signals: I. The Basic Framework. CoRR Cheng Tai, Weinan E
2014	Misc	`conf`	Fire sale in financial networks. CISS Haoshu Tian, Weinan E
2013	J	`jnl`	Efficient iterative method for solving the Dirac-Kohn-Sham density functional theory. J. Comput. Phys. Lin Lin, Sihong Shao, Weinan E
2012	J	`jnl`	Adaptive local basis set for Kohn-Sham density functional theory in a discontinuous Galerkin framework I: Total energy calculation. J. Comput. Phys. Lin Lin, Jianfeng Lu, Lexing Ying, Weinan E
2012	J	`jnl`	Optimized local basis set for Kohn-Sham density functional theory. J. Comput. Phys. Lin Lin, Jianfeng Lu, Lexing Ying, Weinan E
2012	J	`jnl`	The Landscape of Complex Networks CoRR Weinan E, Jianfeng Lu, Yuan Yao
2012	J	`jnl`	The heterogeneous multiscale method. Acta Numer. Assyr Abdulle, Weinan E, Björn Engquist, Eric Vanden-Eijnden
2011	J	`jnl`	A Fast Parallel Algorithm for Selected Inversion of Structured Sparse Matrices with Application to 2D Electronic Structure Calculations. SIAM J. Sci. Comput. Lin Lin, Chao Yang, Jianfeng Lu, Lexing Ying, Weinan E
2011	Misc	`conf`	Failure of random materials: a large deviation and computational study. WSC Jingchen Liu, Rohit Patra, Xiang Zhou, Weinan E
2011	J	`jnl`	Multiscale modeling. Scholarpedia Weinan E, Jianfeng Lu
2011	J	`jnl`	SelInv - An Algorithm for Selected Inversion of a Sparse Symmetric Matrix. ACM Trans. Math. Softw. Lin Lin, Chao Yang, Juan C. Meza, Jianfeng Lu, Lexing Ying, Weinan E
2010	J	`jnl`	A multiscale coupling method for the modeling of dynamics of solids with application to brittle cracks. J. Comput. Phys. Xiantao Li, Jerry Zhijian Yang, Weinan E
2010	J	`jnl`	A numerical method for the study of nucleation of ordered phases. J. Comput. Phys. Ling Lin, Xiuyuan Cheng, Weinan E, An-Chang Shi, Pingwen Zhang
2009	J	`jnl`	A general strategy for designing seamless multiscale methods. J. Comput. Phys. Weinan E, Weiqing Ren, Eric Vanden-Eijnden
2007	J	`jnl`	A discontinuous Galerkin implementation of a domain decomposition method for kinetic-hydrodynamic coupling multiscale problems in gas dynamics and device simulations. J. Comput. Phys. Shanqin Chen, Weinan E, Yunxian Liu, Chi-Wang Shu
2007	J	`jnl`	Nested stochastic simulation algorithms for chemical kinetic systems with multiple time scales. J. Comput. Phys. Weinan E, Di Liu, Eric Vanden-Eijnden
2007	J	`jnl`	The local microscale problem in the multiscale modeling of strongly heterogeneous media: Effects of boundary conditions and cell size. J. Comput. Phys. Xingye Yue, Weinan E
2005	J	`jnl`	The Heterogeneous Multiscale Method Based on the Discontinuous Galerkin Method for Hyperbolic and Parabolic Problems. Multiscale Model. Simul. Shanqin Chen, Weinan E, Chi-Wang Shu
2002	J	`jnl`	Projection method III: Spatial discretization on the staggered grid. Math. Comput. Weinan E, Jian-Guo Liu
2001	J	`jnl`	Simple finite element method in vorticity formulation for incompressible flows. Math. Comput. Jian-Guo Liu, Weinan E
2000	J	`jnl`	Numerical Methods for the Landau-Lifshitz Equation. SIAM J. Numer. Anal. Weinan E, Xiao-Ping Wang