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Quantum Entanglement in Deep Learning Architectures
v1v2v3 (latest)

Quantum Entanglement in Deep Learning Architectures

26 March 2018
Yoav Levine
Or Sharir
Nadav Cohen
Amnon Shashua
ArXiv (abs)PDFHTML

Papers citing "Quantum Entanglement in Deep Learning Architectures"

11 / 61 papers shown
Advances in Quantum Deep Learning: An Overview
Advances in Quantum Deep Learning: An Overview
Siddhant Garg
Goutham Ramakrishnan
157
60
0
08 May 2020
A Tensor Network Approach to Finite Markov Decision Processes
A Tensor Network Approach to Finite Markov Decision Processes
E. Gillman
Dominic C. Rose
J. P. Garrahan
159
4
0
12 Feb 2020
Neural network wave functions and the sign problem
Neural network wave functions and the sign problemPhysical Review Research (PRResearch), 2020
A. Szabó
C. Castelnovo
184
81
0
11 Feb 2020
Parameterized quantum circuits as machine learning models
Parameterized quantum circuits as machine learning modelsQuantum Science and Technology (QST), 2019
Marcello Benedetti
Erika Lloyd
Stefan H. Sack
Mattia Fiorentini
480
1,084
0
18 Jun 2019
TensorNetwork for Machine Learning
TensorNetwork for Machine Learning
Stavros Efthymiou
Jack Hidary
Stefan Leichenauer
172
72
0
07 Jun 2019
Number-State Preserving Tensor Networks as Classifiers for Supervised
  Learning
Number-State Preserving Tensor Networks as Classifiers for Supervised LearningFrontiers of Physics (FP), 2019
G. Evenbly
142
12
0
15 May 2019
TensorNetwork on TensorFlow: A Spin Chain Application Using Tree Tensor
  Networks
TensorNetwork on TensorFlow: A Spin Chain Application Using Tree Tensor Networks
A. Milsted
M. Ganahl
Stefan Leichenauer
Jack Hidary
G. Vidal
218
17
0
03 May 2019
TensorNetwork: A Library for Physics and Machine Learning
TensorNetwork: A Library for Physics and Machine Learning
Chase Roberts
A. Milsted
M. Ganahl
Adam Zalcman
Bruce Fontaine
Yijian Zou
Jack Hidary
G. Vidal
Stefan Leichenauer
AI4CEPINN
144
112
0
03 May 2019
Deep autoregressive models for the efficient variational simulation of
  many-body quantum systems
Deep autoregressive models for the efficient variational simulation of many-body quantum systemsPhysical Review Letters (PRL), 2019
Or Sharir
Yoav Levine
Noam Wies
Giuseppe Carleo
Amnon Shashua
382
221
0
11 Feb 2019
From probabilistic graphical models to generalized tensor networks for
  supervised learning
From probabilistic graphical models to generalized tensor networks for supervised learning
I. Glasser
Nicola Pancotti
J. I. Cirac
AI4CE
222
82
0
15 Jun 2018
Opening the black box of deep learning
Opening the black box of deep learning
Dian Lei
Xiaoxiao Chen
Jianfei Zhao
AI4CEPINN
157
28
0
22 May 2018
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