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Visualizing Neural Network Developing Perturbation Theory

Visualizing Neural Network Developing Perturbation Theory

12 February 2018
Yadong Wu
Pengfei Zhang
Huitao Shen
H. Zhai
ArXivPDFHTML

Papers citing "Visualizing Neural Network Developing Perturbation Theory"

8 / 8 papers shown
Title
Learning Disordered Topological Phases by Statistical Recovery of
  Symmetry
Learning Disordered Topological Phases by Statistical Recovery of Symmetry
N. Yoshioka
Y. Akagi
H. Katsura
43
55
0
18 Sep 2017
Machine Learning Topological Invariants with Neural Networks
Machine Learning Topological Invariants with Neural Networks
Pengfei Zhang
Huitao Shen
H. Zhai
56
198
0
30 Aug 2017
Unsupervised learning of phase transitions: from principal component
  analysis to variational autoencoders
Unsupervised learning of phase transitions: from principal component analysis to variational autoencoders
S. J. Wetzel
SSL
DRL
34
315
0
07 Mar 2017
Deep learning and the Schrödinger equation
Deep learning and the Schrödinger equation
Kyle Mills
M. Spanner
Isaac Tamblyn
38
140
0
05 Feb 2017
Recommender Engine for Continuous Time Quantum Monte Carlo Methods
Recommender Engine for Continuous Time Quantum Monte Carlo Methods
Li Huang
Yi-feng Yang
Lei Wang
38
30
0
06 Dec 2016
Accelerate Monte Carlo Simulations with Restricted Boltzmann Machines
Accelerate Monte Carlo Simulations with Restricted Boltzmann Machines
Li Huang
Lei Wang
AI4CE
32
199
0
10 Oct 2016
Discovering Phase Transitions with Unsupervised Learning
Discovering Phase Transitions with Unsupervised Learning
Lei Wang
26
437
0
01 Jun 2016
Machine learning for many-body physics: The case of the Anderson
  impurity model
Machine learning for many-body physics: The case of the Anderson impurity model
L. Arsenault
A. Lopez-Bezanilla
O. A. von Lilienfeld
A. Millis
AI4CE
53
108
0
05 Aug 2014
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