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1712.03641
Cited By
DeePMD-kit: A deep learning package for many-body potential energy representation and molecular dynamics
11 December 2017
Han Wang
Linfeng Zhang
Jiequn Han
E. Weinan
AI4CE
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Papers citing
"DeePMD-kit: A deep learning package for many-body potential energy representation and molecular dynamics"
21 / 21 papers shown
Title
Data Fusion of Deep Learned Molecular Embeddings for Property Prediction
Robert Appleton
Brian C Barnes
Alejandro Strachan
FedML
AI4CE
34
0
0
09 Apr 2025
A practical guide to machine learning interatomic potentials -- Status and future
Ryan Jacobs
D. Morgan
Siamak Attarian
Jun Meng
Chen Shen
...
K. J. Schmidt
So Takamoto
Aidan Thompson
Julia Westermayr
Brandon M. Wood
59
4
0
12 Mar 2025
Learning local equivariant representations for quantum operators
Zhanghao Zhouyin
Zixi Gan
MingKang Liu
S. K. Pandey
Linfeng Zhang
Qiangqiang Gu
85
3
0
28 Jan 2025
FastCHGNet: Training one Universal Interatomic Potential to 1.5 Hours with 32 GPUs
Yuanchang Zhou
Siyu Hu
Chen Wang
Lin-Wang Wang
Guangming Tan
Weile Jia
AI4CE
GNN
52
0
0
30 Dec 2024
Neural Network Matrix Product Operator: A Multi-Dimensionally Integrable Machine Learning Potential
Kentaro Hino
Yuki Kurashige
34
0
0
31 Oct 2024
chemtrain: Learning Deep Potential Models via Automatic Differentiation and Statistical Physics
Paul Fuchs
Stephan Thaler
Sebastien Röcken
Julija Zavadlav
DiffM
72
6
0
28 Aug 2024
PWDFT-SW: Extending the Limit of Plane-Wave DFT Calculations to 16K Atoms on the New Sunway Supercomputer
Qingcai Jiang
Zhenwei Cao
Junshi Chen
Xinming Qin
Wei Hu
Hong An
Jinlong Yang
15
2
0
16 Jun 2024
Machine-Learned Atomic Cluster Expansion Potentials for Fast and Quantum-Accurate Thermal Simulations of Wurtzite AlN
Guang Yang
Yuan Liu
Lei Yang
Bingyang Cao
AI4CE
34
6
0
20 Nov 2023
A Heterogeneous Parallel Non-von Neumann Architecture System for Accurate and Efficient Machine Learning Molecular Dynamics
Zhuoying Zhao
Ziling Tan
Pinghui Mo
Xiaonan Wang
Dan Zhao
Xin Zhang
Ming Tao
Jie Liu
21
1
0
26 Mar 2023
Neural DAEs: Constrained neural networks
Tue Boesen
E. Haber
Uri M. Ascher
33
3
0
25 Nov 2022
Utilising physics-guided deep learning to overcome data scarcity
Jinshuai Bai
Laith Alzubaidi
Qingxia Wang
E. Kuhl
Bennamoun
Yuantong T. Gu
PINN
AI4CE
31
3
0
24 Nov 2022
Unifying O(3) Equivariant Neural Networks Design with Tensor-Network Formalism
Zimu Li
Zihan Pengmei
Han Zheng
Erik H. Thiede
Junyu Liu
Risi Kondor
29
2
0
14 Nov 2022
Hyperactive Learning (HAL) for Data-Driven Interatomic Potentials
Cas van der Oord
Matthias Sachs
D. P. Kovács
Christoph Ortner
Gábor Csányi
41
64
0
09 Oct 2022
AI-coupled HPC Workflows
S. Jha
V. Pascuzzi
Matteo Turilli
24
9
0
24 Aug 2022
Edge-based Tensor prediction via graph neural networks
Yang Zhong
Hongyu Yu
X. Gong
H. Xiang
13
2
0
15 Jan 2022
Graph Neural Networks Accelerated Molecular Dynamics
Zijie Li
Kazem Meidani
Prakarsh Yadav
A. Farimani
GNN
AI4CE
21
53
0
06 Dec 2021
Complex Spin Hamiltonian Represented by Artificial Neural Network
Hongyu Yu
Changsong Xu
Feng Lou
L. Bellaiche
Zhenpeng Hu
X. Gong
H. Xiang
26
15
0
02 Oct 2021
Symmetry-adapted graph neural networks for constructing molecular dynamics force fields
Zun Wang
Chong Wang
Sibo Zhao
Shiqiao Du
Yong Xu
B. Gu
W. Duan
AI4CE
27
14
0
08 Jan 2021
Learning Thermodynamically Stable and Galilean Invariant Partial Differential Equations for Non-equilibrium Flows
Juntao Huang
Zhiting Ma
Y. Zhou
W. Yong
AI4CE
35
16
0
28 Sep 2020
Machine learning for electronically excited states of molecules
Julia Westermayr
P. Marquetand
17
257
0
10 Jul 2020
Active Learning of Uniformly Accurate Inter-atomic Potentials for Materials Simulation
Linfeng Zhang
De-Ye Lin
Han Wang
R. Car
E. Weinan
9
326
0
28 Oct 2018
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