Numerical Methods for the Landau-Lifshitz Equation. - Weinan E; Xiao-Ping Wang 002 (SIAM J. Numer. Anal., 2000)

Simple finite element method in vorticity formulation for incompressible flows. - Jian-Guo Liu 006; Weinan E (Math. Comput., 2001)

Projection method III: Spatial discretization on the staggered grid. - Weinan E; Jian-Guo Liu 006 (Math. Comput., 2002)

The Heterogeneous Multiscale Method Based on the Discontinuous Galerkin Method for Hyperbolic and Parabolic Problems. - Shanqin Chen; Weinan E; Chi-Wang Shu (Multiscale Model. Simul., 2005)

A discontinuous Galerkin implementation of a domain decomposition method for kinetic-hydrodynamic coupling multiscale problems in gas dynamics and device simulations. - Shanqin Chen; Weinan E; Yunxian Liu; Chi-Wang Shu (J. Comput. Phys., 2007)

Nested stochastic simulation algorithms for chemical kinetic systems with multiple time scales. - Weinan E; Di Liu; Eric Vanden-Eijnden (J. Comput. Phys., 2007)

The local microscale problem in the multiscale modeling of strongly heterogeneous media: Effects of boundary conditions and cell size. - Xingye Yue; Weinan E (J. Comput. Phys., 2007)

A general strategy for designing seamless multiscale methods. - Weinan E; Weiqing Ren; Eric Vanden-Eijnden (J. Comput. Phys., 2009)

A multiscale coupling method for the modeling of dynamics of solids with application to brittle cracks. - Xiantao Li; Jerry Zhijian Yang; Weinan E (J. Comput. Phys., 2010)

A numerical method for the study of nucleation of ordered phases. - Ling Lin; Xiuyuan Cheng; Weinan E; An-Chang Shi; Pingwen Zhang (J. Comput. Phys., 2010)

Failure of random materials: a large deviation and computational study. - Jingchen Liu; Rohit Patra; Xiang Zhou 001; Weinan E (WSC, 2011)

Multiscale modeling. - Weinan E; Jianfeng Lu 001 (Scholarpedia, 2011)

A Fast Parallel Algorithm for Selected Inversion of Structured Sparse Matrices with Application to 2D Electronic Structure Calculations. - Lin Lin 001; Chao Yang 001; Jianfeng Lu 001; Lexing Ying; Weinan E (SIAM J. Sci. Comput., 2011)

SelInv - An Algorithm for Selected Inversion of a Sparse Symmetric Matrix. - Lin Lin 001; Chao Yang 001; Juan C. Meza; Jianfeng Lu 001; Lexing Ying; Weinan E (ACM Trans. Math. Softw., 2011)

The heterogeneous multiscale method. - Assyr Abdulle; Weinan E; Björn Engquist; Eric Vanden-Eijnden (Acta Numer., 2012)

The Landscape of Complex Networks - Weinan E; Jianfeng Lu 001; Yuan Yao (CoRR, 2012)

Adaptive local basis set for Kohn-Sham density functional theory in a discontinuous Galerkin framework I: Total energy calculation. - Lin Lin 001; Jianfeng Lu 001; Lexing Ying; Weinan E (J. Comput. Phys., 2012)

Optimized local basis set for Kohn-Sham density functional theory. - Lin Lin 001; Jianfeng Lu 001; Lexing Ying; Weinan E (J. Comput. Phys., 2012)

Efficient iterative method for solving the Dirac-Kohn-Sham density functional theory. - Lin Lin 001; Sihong Shao; Weinan E (J. Comput. Phys., 2013)

Fire sale in financial networks. - Haoshu Tian; Weinan E (CISS, 2014)

Dynamics of Stochastic Gradient Algorithms. - Qianxiao Li; Cheng Tai; Weinan E (CoRR, 2015)

Functional Frank-Wolfe Boosting for General Loss Functions. - Chu Wang; Yingfei Wang; Weinan E; Robert E. Schapire (CoRR, 2015)

Noisy Hegselmann-Krause systems: Phase transition and the 2R-conjecture. - Chu Wang; Qianxiao Li; Weinan E; Bernard Chazelle (CDC, 2016)

Deep Learning Approximation for Stochastic Control Problems. - Jiequn Han; Weinan E (CoRR, 2016)

Convolutional neural networks with low-rank regularization. - Cheng Tai; Tong Xiao; Xiaogang Wang 001; Weinan E (ICLR (Poster), 2016)

Multiscale Adaptive Representation of Signals: I. The Basic Framework. - Cheng Tai; Weinan E (J. Mach. Learn. Res., 2016)

Stochastic Modified Equations and Adaptive Stochastic Gradient Algorithms. - Qianxiao Li; Cheng Tai; Weinan E (ICML, 2017)

Joint Learning of Response Ranking and Next Utterance Suggestion in Human-Computer Conversation System. - Rui Yan 001; Dongyan Zhao 001; Weinan E (SIGIR, 2017)

Deep learning-based numerical methods for high-dimensional parabolic partial differential equations and backward stochastic differential equations. - Weinan E; Jiequn Han; Arnulf Jentzen (CoRR, 2017)

Overcoming the curse of dimensionality: Solving high-dimensional partial differential equations using deep learning. - Jiequn Han; Arnulf Jentzen; Weinan E (CoRR, 2017)

Towards Understanding Generalization of Deep Learning: Perspective of Loss Landscapes. - Lei Wu; Zhanxing Zhu; Weinan E (CoRR, 2017)

Deep Potential Molecular Dynamics: a scalable model with the accuracy of quantum mechanics. - Linfeng Zhang 002; Jiequn Han; Han Wang 006; Roberto Car; Weinan E (CoRR, 2017)

The Deep Ritz method: A deep learning-based numerical algorithm for solving variational problems. - Weinan E; Bing Yu (CoRR, 2017)

Reinforced dynamics for enhanced sampling in large atomic and molecular systems. I. Basic Methodology. - Linfeng Zhang 002; Han Wang 006; Weinan E (CoRR, 2017)

Maximum Principle Based Algorithms for Deep Learning. - Qianxiao Li; Long Chen; Cheng Tai; Weinan E (J. Mach. Learn. Res., 2017)

How SGD Selects the Global Minima in Over-parameterized Learning: A Dynamical Stability Perspective. - Lei Wu; Chao Ma 012; Weinan E (NeurIPS, 2018)

End-to-end Symmetry Preserving Inter-atomic Potential Energy Model for Finite and Extended Systems. - Linfeng Zhang 002; Jiequn Han; Han Wang 006; Wissam Saidi; Roberto Car; Weinan E (NeurIPS, 2018)

Understanding and Enhancing the Transferability of Adversarial Examples. - Lei Wu; Zhanxing Zhu; Cheng Tai; Weinan E (CoRR, 2018)

Exponential Convergence of the Deep Neural Network Approximation for Analytic Functions. - Weinan E; Qingcan Wang (CoRR, 2018)

A Mean-Field Optimal Control Formulation of Deep Learning. - Weinan E; Jiequn Han; Qianxiao Li (CoRR, 2018)

Model Reduction with Memory and the Machine Learning of Dynamical Systems. - Chao Ma 012; Jianchun Wang; Weinan E (CoRR, 2018)

Monge-Ampère Flow for Generative Modeling. - Linfeng Zhang 002; Weinan E; Lei Wang (CoRR, 2018)

A Priori Estimates of the Generalization Error for Two-layer Neural Networks. - Weinan E; Chao Ma 012; Lei Wu (CoRR, 2018)

Active Learning of Uniformly Accurate Inter-atomic Potentials for Materials Simulation. - Linfeng Zhang 002; De-Ye Lin; Han Wang 006; Roberto Car; Weinan E (CoRR, 2018)

DeePMD-kit: A deep learning package for many-body potential energy representation and molecular dynamics. - Han Wang 006; Linfeng Zhang 002; Jiequn Han; Weinan E (Comput. Phys. Commun., 2018)

A Priori Estimates of the Population Risk for Residual Networks. - Weinan E; Chao Ma 012; Qingcan Wang (CoRR, 2019)

A Comparative Analysis of the Optimization and Generalization Property of Two-layer Neural Network and Random Feature Models Under Gradient Descent Dynamics. - Weinan E; Chao Ma 012; Lei Wu (CoRR, 2019)

Analysis of the Gradient Descent Algorithm for a Deep Neural Network Model with Skip-connections. - Weinan E; Chao Ma 012; Qingcan Wang; Lei Wu (CoRR, 2019)

Barron Spaces and the Compositional Function Spaces for Neural Network Models. - Weinan E; Chao Ma 012; Lei Wu (CoRR, 2019)

A Mathematical Model for Linguistic Universals. - Weinan E; Yajun Zhou (CoRR, 2019)

On the Generalization Properties of Minimum-norm Solutions for Over-parameterized Neural Network Models. - Weinan E; Chao Ma 012; Lei Wu (CoRR, 2019)

Machine Learning from a Continuous Viewpoint. - Weinan E; Chao Ma 012; Lei Wu (CoRR, 2019)

Solving many-electron Schrödinger equation using deep neural networks. - Jiequn Han; Linfeng Zhang 002; Weinan E (J. Comput. Phys., 2019)

Stochastic Modified Equations and Dynamics of Stochastic Gradient Algorithms I: Mathematical Foundations. - Qianxiao Li; Cheng Tai; Weinan E (J. Mach. Learn. Res., 2019)

Machine Learning Approximation Algorithms for High-Dimensional Fully Nonlinear Partial Differential Equations and Second-order Backward Stochastic Differential Equations. - Christian Beck; Weinan E; Arnulf Jentzen (J. Nonlinear Sci., 2019)

On Multilevel Picard Numerical Approximations for High-Dimensional Nonlinear Parabolic Partial Differential Equations and High-Dimensional Nonlinear Backward Stochastic Differential Equations. - Weinan E; Martin Hutzenthaler; Arnulf Jentzen; Thomas Kruse (J. Sci. Comput., 2019)

A Priori Estimates of the Generalization Error for Autoencoders. - Zehao Don; Weinan E; Chao Ma 012 (ICASSP, 2020)

The Slow Deterioration of the Generalization Error of the Random Feature Model. - Chao Ma 012; Lei Wu; Weinan E (MSML, 2020)

Towards Theoretically Understanding Why Sgd Generalizes Better Than Adam in Deep Learning. - Pan Zhou 002; Jiashi Feng; Chao Ma 012; Caiming Xiong; Steven Chu-Hong Hoi; Weinan E (NeurIPS, 2020)

Pushing the limit of molecular dynamics with ab initio accuracy to 100 million atoms with machine learning. - Weile Jia; Han Wang 006; Mohan Chen 002; Denghui Lu; Lin Lin 001; Roberto Car; Weinan E; Linfeng Zhang 002 (SC, 2020)

Machine learning based non-Newtonian fluid model with molecular fidelity. - Huan Lei; Lei Wu; Weinan E (CoRR, 2020)

86 PFLOPS Deep Potential Molecular Dynamics simulation of 100 million atoms with ab initio accuracy. - Denghui Lu; Han Wang 006; Mohan Chen 002; Jiduan Liu; Lin Lin 001; Roberto Car; Weinan E; Weile Jia; Linfeng Zhang 002 (CoRR, 2020)

Kolmogorov Width Decay and Poor Approximators in Machine Learning: Shallow Neural Networks, Random Feature Models and Neural Tangent Kernels. - Weinan E; Stephan Wojtowytsch (CoRR, 2020)

Integrating Machine Learning with Physics-Based Modeling. - Weinan E; Jiequn Han; Linfeng Zhang 002 (CoRR, 2020)

Representation formulas and pointwise properties for Barron functions. - Weinan E; Stephan Wojtowytsch (CoRR, 2020)

The Quenching-Activation Behavior of the Gradient Descent Dynamics for Two-layer Neural Network Models. - Chao Ma 012; Lei Wu; Weinan E (CoRR, 2020)

Coarse-grained spectral projection (CGSP): A scalable and parallelizable deep learning-based approach to quantum unitary dynamics. - Pinchen Xie; Weinan E (CoRR, 2020)

On the Banach spaces associated with multi-layer ReLU networks: Function representation, approximation theory and gradient descent dynamics. - Weinan E; Stephan Wojtowytsch (CoRR, 2020)

DeePKS: a comprehensive data-driven approach towards chemically accurate density functional theory. - Yixiao Chen; Linfeng Zhang 002; Han Wang 006; Weinan E (CoRR, 2020)

Algorithms for Solving High Dimensional PDEs: From Nonlinear Monte Carlo to Machine Learning. - Weinan E; Jiequn Han; Arnulf Jentzen (CoRR, 2020)

OnsagerNet: Learning Stable and Interpretable Dynamics using a Generalized Onsager Principle. - Haijun Yu; Xinyuan Tian; Weinan E; Qianxiao Li (CoRR, 2020)

Towards a Mathematical Understanding of Neural Network-Based Machine Learning: what we know and what we don't. - Weinan E; Chao Ma 012; Stephan Wojtowytsch; Lei Wu (CoRR, 2020)

A priori estimates for classification problems using neural networks. - Weinan E; Stephan Wojtowytsch (CoRR, 2020)

Machine Learning and Computational Mathematics. - Weinan E (CoRR, 2020)

The Knowledge Graph for Macroeconomic Analysis with Alternative Big Data. - Yucheng Yang; Yue Pang; Guanhua Huang; Weinan E (CoRR, 2020)

Interpretable Neural Networks for Panel Data Analysis in Economics. - Yucheng Yang; Zhong Zheng; Weinan E (CoRR, 2020)

Some observations on partial differential equations in Barron and multi-layer spaces. - Weinan E; Stephan Wojtowytsch (CoRR, 2020)

On the emergence of tetrahedral symmetry in the final and penultimate layers of neural network classifiers. - Weinan E; Stephan Wojtowytsch (CoRR, 2020)

A deep learning-based ODE solver for chemical kinetics. - Tianhan Zhang; Yaoyu Zhang; Weinan E; Yiguang Ju (CoRR, 2020)

DP-GEN: A concurrent learning platform for the generation of reliable deep learning based potential energy models. - Yuzhi Zhang; Haidi Wang; Weijie Chen 003; Jinzhe Zeng; Linfeng Zhang 002; Han Wang 006; Weinan E (Comput. Phys. Commun., 2020)

Can Shallow Neural Networks Beat the Curse of Dimensionality? A Mean Field Training Perspective. - Stephan Wojtowytsch; Weinan E (IEEE Trans. Artif. Intell., 2020)

On the Curse of Memory in Recurrent Neural Networks: Approximation and Optimization Analysis. - Zhong Li 004; Jiequn Han; Weinan E; Qianxiao Li (ICLR, 2021)

A Qualitative Study of the Dynamic Behavior for Adaptive Gradient Algorithms. - Chao Ma 012; Lei Wu; Weinan E (MSML, 2021)

Some observations on high-dimensional partial differential equations with Barron data. - Weinan E; Stephan Wojtowytsch (MSML, 2021)

On the emergence of simplex symmetry in the final and penultimate layers of neural network classifiers. - Weinan E; Stephan Wojtowytsch (MSML, 2021)

Generalization and Memorization: The Bias Potential Model. - Hongkang Yang; Weinan E (MSML, 2021)

An L2 Analysis of Reinforcement Learning in High Dimensions with Kernel and Neural Network Approximation. - Jihao Long; Jiequn Han; Weinan E (CoRR, 2021)

Generalization Error of GAN from the Discriminator's Perspective. - Hongkang Yang; Weinan E (CoRR, 2021)

DeepHAM: A Global Solution Method for Heterogeneous Agent Models with Aggregate Shocks. - Jiequn Han; Yucheng Yang; Weinan E (CoRR, 2021)

DeePN2: A deep learning-based non-Newtonian hydrodynamic model. - Lidong Fang; Pei Ge; Lei Zhang; Huan Lei; Weinan E (CoRR, 2021)

86 PFLOPS Deep Potential Molecular Dynamics simulation of 100 million atoms with ab initio accuracy. - Denghui Lu; Han Wang 006; Mohan Chen 002; Lin Lin 001; Roberto Car; Weinan E; Weile Jia; Linfeng Zhang 002 (Comput. Phys. Commun., 2021)

A Machine Learning Enhanced Algorithm for the Optimal Landing Problem. - Yaohua Zang; Jihao Long; Xuanxi Zhang; Wei Hu; Weinan E; Jiequn Han (MSML, 2022)

A deep learning-based model reduction (DeePMR) method for simplifying chemical kinetics. - Zhiwei Wang; Yaoyu Zhang; Yiguang Ju; Weinan E; Zhi-Qin John Xu; Tianhan Zhang (CoRR, 2022)

A multi-scale sampling method for accurate and robust deep neural network to predict combustion chemical kinetics. - Tianhan Zhang; Yuxiao Yi; Yifan Xu; Zhi X. Chen; Yaoyu Zhang; Weinan E; Zhi-Qin John Xu (CoRR, 2022)

Bridging Traditional and Machine Learning-based Algorithms for Solving PDEs: The Random Feature Method. - Jingrun Chen; Xurong Chi; Weinan E; Zhouwang Yang (CoRR, 2022)

Approximation and Optimization Theory for Linear Continuous-Time Recurrent Neural Networks. - Zhong Li 004; Jiequn Han; Weinan E; Qianxiao Li (J. Mach. Learn. Res., 2022)

Efficient sampling of high-dimensional free energy landscapes using adaptive reinforced dynamics. - Dongdong Wang; Yanze Wang; Junhan Chang; Linfeng Zhang 002; Han Wang 006; Weinan E (Nat. Comput. Sci., 2022)

A Mathematical Model for Universal Semantics. - Weinan E; Yajun Zhou (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Introduction to Data Science - Gaoyan Ou; Zhanxing Zhu; Bin Dong 001; Weinan E; Binyang Li; Shumin Shi (WorldScientific, 2023)

An Iteratively Parallel Generation Method with the Pre-Filling Strategy for Document-level Event Extraction. - Guanhua Huang; Runxin Xu; Ying Zeng; Jiaze Chen; Zhouwang Yang; Weinan E (EMNLP, 2023)

AMP: A unified framework boosting low resource automatic speech recognition. - Zeping Min; Qian Ge; Zhong Li 004; Weinan E (CoRR, 2023)

The Random Feature Method for Time-dependent Problems. - Jingrun Chen; Weinan E; Yixin Luo (CoRR, 2023)

Machine-Learned Invertible Coarse Graining for Multiscale Molecular Modeling. - Jun Zhang 071; Xiaohan Lin; Weinan E; Yi Qin Gao (CoRR, 2023)

DeePKS-kit: A package for developing machine learning-based chemically accurate energy and density functional models. - Yixiao Chen; Linfeng Zhang 002; Han Wang 006; Weinan E (Comput. Phys. Commun., 2023)

Exploring Molecular Pretraining Model at Scale. - Xiaohong Ji; Zhen Wang; Zhifeng Gao; Hang Zheng; Linfeng Zhang 002; Guolin Ke; Weinan E (NeurIPS, 2024)

Improving Generalization and Convergence by Enhancing Implicit Regularization. - Mingze Wang; Jinbo Wang 003; Haotian He; Zilin Wang; Guanhua Huang; Feiyu Xiong; Zhiyu Li; Weinan E; Lei Wu (NeurIPS, 2024)

Understanding the Expressive Power and Mechanisms of Transformer for Sequence Modeling. - Mingze Wang; Weinan E (NeurIPS, 2024)

Solving multiscale dynamical systems by deep learning. - Zhi-Qin John Xu; Junjie Yao; Yuxiao Yi; Liangkai Hang; Weinan E; Yaoyu Zhang; Tianhan Zhang (CoRR, 2024)

Anchor function: a type of benchmark functions for studying language models. - Zhongwang Zhang; Zhiwei Wang; Junjie Yao; Zhangchen Zhou; Xiaolong Li; Weinan E; Zhi-Qin John Xu (CoRR, 2024)

Coarse-graining conformational dynamics with multi-dimensional generalized Langevin equation: how, when, and why. - Pinchen Xie; Yunrui Qiu; Weinan E (CoRR, 2024)

Uni-Mol2: Exploring Molecular Pretraining Model at Scale. - Xiaohong Ji; Zhen Wang; Zhifeng Gao; Hang Zheng; Linfeng Zhang 002; Guolin Ke; Weinan E (CoRR, 2024)

Memory3: Language Modeling with Explicit Memory. - Hongkang Yang; Zehao Lin; Wenjin Wang 003; Hao Wu 022; Zhiyu Li; Bo Tang 011; Wenqiang Wei; Jinbo Wang 003; Zeyun Tang; Shichao Song; Chenyang Xi; Yu Yu; et al. (CoRR, 2024)

Uni-ELF: A Multi-Level Representation Learning Framework for Electrolyte Formulation Design. - Boshen Zeng; Sian Chen; Xinxin Liu; Changhong Chen; Bin Deng; Xiaoxu Wang; Zhifeng Gao; Yuzhi Zhang; Weinan E; Linfeng Zhang 002 (CoRR, 2024)

How Transformers Implement Induction Heads: Approximation and Optimization Analysis. - Mingze Wang; Ruoxi Yu; Weinan E; Lei Wu (CoRR, 2024)

Intelligent System for Automated Molecular Patent Infringement Assessment. - Yaorui Shi; Sihang Li 002; Taiyan Zhang; Xi Fang; Jiankun Wang 011; Zhiyuan Liu 001; Guojiang Zhao; Zhengdan Zhu; Zhifeng Gao; Renxin Zhong; Linfeng Zhang 002; Guolin Ke; et al. (CoRR, 2024)

Accurate Conformation Sampling via Protein Structural Diffusion. - Jiahao Fan; Ziyao Li; Eric Alcaide; Guolin Ke; Huaqing Huang; Weinan E (J. Chem. Inf. Model., 2024)

PaSa: An LLM Agent for Comprehensive Academic Paper Search. - Yichen He; Guanhua Huang; Peiyuan Feng; Yuan Lin; Yuchen Zhang; Hang Li; Weinan E (ACL (1), 2025)

Learning Free Terminal Time Optimal Closed-loop Control of Manipulators. - Wei Hu; Yue Zhao; Weinan E; Jiequn Han; Jihao Long (ACC, 2025)

Solving optimal control problems of rigid-body dynamics with collisions using the hybrid minimum principle. - Wei Hu; Jihao Long; Yaohua Zang; Weinan E; Jiequn Han (Commun. Nonlinear Sci. Numer. Simul., 2025)

Solving multiscale dynamical systems by deep learning. - Junjie Yao; Yuxiao Yi; Liangkai Hang; Weinan E; Weizong Wang; Yaoyu Zhang; Tianhan Zhang; Zhi-Qin John Xu (Comput. Phys. Commun., 2025)

Strategic priorities for transformative progress in advancing biology with proteomics and artificial intelligence. - Yingying Sun; Jun A; Zhiwei Liu; Rui Sun; Liujia Qian; Samuel H. Payne; Wout Bittremieux; Markus Ralser; Chen Li 021; Yi Chen; Zhen Dong; Yasset Pérez-Riverol; et al. (CoRR, 2025)

The Sharpness Disparity Principle in Transformers for Accelerating Language Model Pre-Training. - Jinbo Wang 003; Mingze Wang; Zhanpeng Zhou; Junchi Yan; Weinan E; Lei Wu (CoRR, 2025)

Uni-3DAR: Unified 3D Generation and Understanding via Autoregression on Compressed Spatial Tokens. - Shuqi Lu; Haowei Lin; Lin Yao 003; Zhifeng Gao; Xiaohong Ji; Weinan E; Linfeng Zhang 002; Guolin Ke (CoRR, 2025)

RARE: Retrieval-Augmented Reasoning Modeling. - Zhengren Wang; Jiayang Yu; Dongsheng Ma; Zhe Chen 024; Yu Wang 027; Zhiyu Li; Feiyu Xiong; Yanfeng Wang 001; Weinan E; Linpeng Tang; Wentao Zhang (CoRR, 2025)

Toward a unified benchmark and framework for deep learning-based prediction of nuclear magnetic resonance chemical shifts. - Fanjie Xu; Wentao Guo; Feng Wang; Lin Yao 003; Hongshuai Wang; Fujie Tang; Zhifeng Gao; Linfeng Zhang 002; Weinan E; Zhong-Qun Tian; Jun Cheng (Nat. Comput. Sci., 2025)

A brief review of the Deep BSDE method for solving high-dimensional partial differential equations. - Jiequn Han; Arnulf Jentzen; Weinan E (CoRR, 2025)

Scalable Complexity Control Facilitates Reasoning Ability of LLMs. - Liangkai Hang; Junjie Yao; Zhiwei Bai; Tianyi Chen; Yang Chen; Rongjie Diao; Hezhou Li; Pengxiao Lin; Zhiwei Wang; Cheng Xu; Zhongwang Zhang; Zhangchen Zhou; et al. (CoRR, 2025)

On the Expressive Power of Mixture-of-Experts for Structured Complex Tasks. - Mingze Wang; Weinan E (CoRR, 2025)

GradPower: Powering Gradients for Faster Language Model Pre-Training. - Mingze Wang; Jinbo Wang 003; Jiaqi Zhang; Wei Wang; Peng Pei; Xunliang Cai; Weinan E; Lei Wu (CoRR, 2025)

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning. - Zexi Liu; Yuzhu Cai; Xinyu Zhu; Yujie Zheng; Runkun Chen; Ying Wen; Yanfeng Wang 001; Weinan E; Siheng Chen (CoRR, 2025)

pUniFind: a unified large pre-trained deep learning model pushing the limit of mass spectra interpretation. - Jiale Zhao; Pengzhi Mao; Kaifei Wang; Yiming Li; Yaping Peng; Ranfei Chen; Shuqi Lu; Xiaohong Ji; Jiaxiang Ding; Xin Zhang; Yucheng Liao; Weinan E; et al. (CoRR, 2025)

SciMaster: Towards General-Purpose Scientific AI Agents, Part I. X-Master as Foundation: Can We Lead on Humanity's Last Exam? - Jingyi Chai; Shuo Tang; Rui Ye 001; Yuwen Du; Xinyu Zhu; Mengcheng Zhou; Yanfeng Wang 001; Weinan E; Yuzhi Zhang; Linfeng Zhang 002; Siheng Chen (CoRR, 2025)

SynBridge: Bridging Reaction States via Discrete Flow for Bidirectional Reaction Prediction. - Haitao Lin; Junjie Wang; Zhifeng Gao; Xiaohong Ji; Rong Zhu; Linfeng Zhang 002; Guolin Ke; Weinan E (CoRR, 2025)