Artikel dengan mandat akses publik - Weinan EPelajari lebih lanjut
Tidak tersedia di mana pun: 3
Modeling subgrid-scale forces by spatial artificial neural networks in large eddy simulation of turbulence
C Xie, J Wang, W E
Physical Review Fluids 5 (5), 054606, 2020
Mandat: National Natural Science Foundation of China
Unraveling the Atomic‐scale Mechanism of Phase Transformations and Structural Evolutions during (de) Lithiation in Si Anodes
F Fu, X Wang, L Zhang, Y Yang, J Chen, B Xu, C Ouyang, S Xu, FZ Dai, ...
Advanced Functional Materials 33 (37), 2303936, 2023
Mandat: National Natural Science Foundation of China
DLODE: a deep learning-based ODE solver for chemistry kinetics
T Zhang, Y Zhang, W E, Y Ju
AIAA Scitech 2021 Forum, 1139, 2021
Mandat: US National Science Foundation, US Department of Defense
Tersedia di suatu tempat: 57
Solving high-dimensional partial differential equations using deep learning
J Han, A Jentzen, W E
Proceedings of the National Academy of Sciences 115 (34), 8505-8510, 2018
Mandat: US Department of Energy, US Department of Defense, National Natural Science …
Deep potential molecular dynamics: a scalable model with the accuracy of quantum mechanics
L Zhang, J Han, H Wang, R Car, W E
Physical review letters 120 (14), 143001, 2018
Mandat: US Department of Energy, US Department of Defense, National Natural Science …
DeePMD-kit: A deep learning package for many-body potential energy representation and molecular dynamics
H Wang, L Zhang, J Han, E Weinan
Computer Physics Communications 228, 178-184, 2018
Mandat: US Department of Energy, US Department of Defense, National Natural Science …
Deep learning-based numerical methods for high-dimensional parabolic partial differential equations and backward stochastic differential equations
J Han, A Jentzen
Communications in mathematics and statistics 5 (4), 349-380, 2017
Mandat: US Department of Energy, US Department of Defense, National Natural Science …
DP-GEN: A concurrent learning platform for the generation of reliable deep learning based potential energy models
Y Zhang, H Wang, W Chen, J Zeng, L Zhang, H Wang, E Weinan
Computer Physics Communications 253, 107206, 2020
Mandat: US Department of Energy, US Department of Defense, National Natural Science …
Active learning of uniformly accurate interatomic potentials for materials simulation
L Zhang, DY Lin, H Wang, R Car, W E
Physical Review Materials 3 (2), 023804, 2019
Mandat: US Department of Energy, US Department of Defense, National Natural Science …
The heterogeneous multiscale method
A Abdulle, E Weinan, B Engquist, E Vanden-Eijnden
Acta Numerica 21, 1-87, 2012
Mandat: Swiss National Science Foundation
Phase diagram of a deep potential water model
L Zhang, H Wang, R Car, W E
Physical review letters 126 (23), 236001, 2021
Mandat: US Department of Energy, US Department of Defense, National Natural Science …
Stochastic modified equations and adaptive stochastic gradient algorithms
Q Li, C Tai, E Weinan
International Conference on Machine Learning, 2101-2110, 2017
Mandat: US Department of Energy, US Department of Defense, National Natural Science …
Pushing the limit of molecular dynamics with ab initio accuracy to 100 million atoms with machine learning
W Jia, H Wang, M Chen, D Lu, L Lin, R Car, E Weinan, L Zhang
SC20: International conference for high performance computing, networking …, 2020
Mandat: US National Science Foundation, US Department of Energy, US Department of …
Machine learning approximation algorithms for high-dimensional fully nonlinear partial differential equations and second-order backward stochastic differential equations
C Beck, W E, A Jentzen
Journal of Nonlinear Science 29, 1563-1619, 2019
Mandat: US Department of Energy, US Department of Defense
Maximum principle based algorithms for deep learning
Q Li, L Chen, C Tai, E Weinan
Journal of Machine Learning Research 18 (165), 1-29, 2018
Mandat: US Department of Energy, US Department of Defense, National Natural Science …
How sgd selects the global minima in over-parameterized learning: A dynamical stability perspective
L Wu, C Ma
Advances in Neural Information Processing Systems 31, 2018
Mandat: US Department of Defense, National Natural Science Foundation of China
Solving many-electron Schrödinger equation using deep neural networks
J Han, L Zhang, E Weinan
Journal of Computational Physics 399, 108929, 2019
Mandat: US Department of Defense, National Natural Science Foundation of China
DeePCG: Constructing coarse-grained models via deep neural networks
L Zhang, J Han, H Wang, R Car
The Journal of chemical physics 149 (3), 2018
Mandat: US Department of Energy, US Department of Defense, National Natural Science …
Stochastic modified equations and dynamics of stochastic gradient algorithms i: Mathematical foundations
Q Li, C Tai, E Weinan
Journal of Machine Learning Research 20 (40), 1-47, 2019
Mandat: US Department of Defense, A*Star, Singapore
86 PFLOPS deep potential molecular dynamics simulation of 100 million atoms with ab initio accuracy
D Lu, H Wang, M Chen, L Lin, R Car, E Weinan, W Jia, L Zhang
Computer Physics Communications 259, 107624, 2021
Mandat: US National Science Foundation, US Department of Energy, US Department of …
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