E Weinan

Research interests

Publications

• DeePMD-kit v2: A software package for deep potential models

  The Journal of Chemical Physics · 2023 · https://doi.org/10.1063/5.0155600

• Phase Diagram of a Deep Potential Water Model

  Physical Review Letters · 2021 · https://doi.org/10.1103/physrevlett.126.236001

• DP-GEN: A concurrent learning platform for the generation of reliable deep learning based potential energy models

  Computer Physics Communications · 2020 · https://doi.org/10.1016/j.cpc.2020.107206

• Machine Learning Approximation Algorithms for High-Dimensional Fully Nonlinear Partial Differential Equations and Second-order Backward Stochastic Differential Equations

  Journal of Nonlinear Science · 2019 · https://doi.org/10.1007/s00332-018-9525-3

• DeePMD-kit: A deep learning package for many-body potential energy representation and molecular dynamics

  Computer Physics Communications · 2018 · https://doi.org/10.1016/j.cpc.2018.03.016

• Solving high-dimensional partial differential equations using deep learning

  Proceedings of the National Academy of Sciences · 2018 · https://doi.org/10.1073/pnas.1718942115

• Deep Potential Molecular Dynamics: A Scalable Model with the Accuracy of Quantum Mechanics

  Physical Review Letters · 2018 · https://doi.org/10.1103/physrevlett.120.143001

• The Deep Ritz Method: A Deep Learning-Based Numerical Algorithm for Solving Variational Problems

  Communications in Mathematics and Statistics · 2018 · https://doi.org/10.1007/s40304-018-0127-z

• A Proposal on Machine Learning via Dynamical Systems

  Communications in Mathematics and Statistics · 2017 · https://doi.org/10.1007/s40304-017-0103-z

• Deep Learning-Based Numerical Methods for High-Dimensional Parabolic Partial Differential Equations and Backward Stochastic Differential Equations

  Communications in Mathematics and Statistics · 2017 · https://doi.org/10.1007/s40304-017-0117-6

• Convolutional neural networks with low-rank regularization

  arXiv (Cornell University) · 2016

• The heterogeneous multiscale method

  Acta Numerica · 2012 · https://doi.org/10.1017/s0962492912000025

• Principles of Multiscale Modeling

  Journal · 2011

• Transition-Path Theory and Path-Finding Algorithms for the Study of Rare Events

  Annual Review of Physical Chemistry · 2008 · https://doi.org/10.1146/annurev.physchem.040808.090412

• Heterogeneous Multiscale Methods: A Review

  Communications in Computational Physics · 2007 · https://doi.org/10.4208/cicp.2007.v2.p367

• Simplified and improved string method for computing the minimum energy paths in barrier-crossing events

  The Journal of Chemical Physics · 2007 · https://doi.org/10.1063/1.2720838

• Towards a Theory of Transition Paths

  Journal of Statistical Physics · 2006 · https://doi.org/10.1007/s10955-005-9003-9

• Finite Temperature String Method for the Study of Rare Events

  The Journal of Physical Chemistry B · 2005 · https://doi.org/10.1021/jp0455430

• Analysis of the heterogeneous multiscale method for elliptic homogenization problems

  Journal of the American Mathematical Society · 2004 · https://doi.org/10.1090/s0894-0347-04-00469-2

• Heterogeneous multiscale method: A general methodology for multiscale modeling

  Physical review. B, Condensed matter · 2003 · https://doi.org/10.1103/physrevb.67.092101

• The Heterognous Multiscale Methods

  Communications in Mathematical Sciences · 2003 · https://doi.org/10.4310/cms.2003.v1.n1.a8

• String method for the study of rare events

  Physical review. B, Condensed matter · 2002 · https://doi.org/10.1103/physrevb.66.052301

• Invariant Measures for Burgers Equation with Stochastic Forcing

  Annals of Mathematics · 2000 · https://doi.org/10.2307/121126

• Generalized variational principles, global weak solutions and behavior with random initial data for systems of conservation laws arising in adhesion particle dynamics

  Communications in Mathematical Physics · 1996 · https://doi.org/10.1007/bf02101897

• Onsager's conjecture on the energy conservation for solutions of Euler's equation

  Communications in Mathematical Physics · 1994 · https://doi.org/10.1007/bf02099744

Current projects

No projects listed.