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Simple and efficient algorithms for training machine learning potentials
  to force data

Simple and efficient algorithms for training machine learning potentials to force data

9 June 2020
Justin S. Smith
Nicholas Lubbers
A. Thompson
K. Barros
ArXiv (abs)PDFHTML

Papers citing "Simple and efficient algorithms for training machine learning potentials to force data"

3 / 3 papers shown
Title
Automated discovery of a robust interatomic potential for aluminum
Automated discovery of a robust interatomic potential for aluminum
Justin S. Smith
B. Nebgen
N. Mathew
Jie Chen
Nicholas Lubbers
...
S. Tretiak
H. Nam
T. Germann
S. Fensin
K. Barros
35
82
0
10 Mar 2020
DeePMD-kit: A deep learning package for many-body potential energy
  representation and molecular dynamics
DeePMD-kit: A deep learning package for many-body potential energy representation and molecular dynamics
Han Wang
Linfeng Zhang
Jiequn Han
E. Weinan
AI4CE
72
1,240
0
11 Dec 2017
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed
  Systems
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems
Martín Abadi
Ashish Agarwal
P. Barham
E. Brevdo
Zhiwen Chen
...
Pete Warden
Martin Wattenberg
Martin Wicke
Yuan Yu
Xiaoqiang Zheng
276
11,151
0
14 Mar 2016
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