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1902.06888
Cited By
Probabilistic Modeling with Matrix Product States
19 February 2019
J. Stokes
John Terilla
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Papers citing
"Probabilistic Modeling with Matrix Product States"
16 / 16 papers shown
Title
Entangling Machine Learning with Quantum Tensor Networks
Constantijn van der Poel
Dan Zhao
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0
09 Jan 2024
Grokking phase transitions in learning local rules with gradient descent
Bojan Žunkovič
E. Ilievski
105
17
0
26 Oct 2022
Deep tensor networks with matrix product operators
Bojan Žunkovič
102
4
0
16 Sep 2022
Tensor Train for Global Optimization Problems in Robotics
Suhan Shetty
Teguh Santoso Lembono
Tobias Löw
Sylvain Calinon
87
12
0
10 Jun 2022
Generative modeling with projected entangled-pair states
Tom Vieijra
L. Vanderstraeten
F. Verstraete
90
20
0
16 Feb 2022
Generalization Metrics for Practical Quantum Advantage in Generative Models
Kaitlin Gili
M. Mauri
A. Perdomo-Ortiz
96
7
0
21 Jan 2022
Explainable Natural Language Processing with Matrix Product States
J. Tangpanitanon
Chanatip Mangkang
P. Bhadola
Yuichiro Minato
D. Angelakis
Thiparat Chotibut
67
5
0
16 Dec 2021
Differentiable Programming of Isometric Tensor Networks
Chenhua Geng
Hong-Ye Hu
Yijian Zou
55
10
0
08 Oct 2021
Probabilistic Graphical Models and Tensor Networks: A Hybrid Framework
Jacob Miller
Geoffrey Roeder
T. Bradley
39
6
0
29 Jun 2021
Quantum Tensor Networks, Stochastic Processes, and Weighted Automata
Siddarth Srinivasan
Sandesh Adhikary
Jacob Miller
Guillaume Rabusseau
Byron Boots
51
15
0
20 Oct 2020
Natural evolution strategies and variational Monte Carlo
Tianchen Zhao
Giuseppe Carleo
J. Stokes
S. Veerapaneni
125
5
0
09 May 2020
Tensor Networks for Probabilistic Sequence Modeling
Jacob Miller
Guillaume Rabusseau
John Terilla
32
5
0
02 Mar 2020
SchrödingeRNN: Generative Modeling of Raw Audio as a Continuously Observed Quantum State
Beñat Mencia Uranga
A. Lamacraft
96
3
0
26 Nov 2019
Modeling Sequences with Quantum States: A Look Under the Hood
T. Bradley
Miles E. Stoudenmire
John Terilla
117
48
0
16 Oct 2019
Expressive power of tensor-network factorizations for probabilistic modeling, with applications from hidden Markov models to quantum machine learning
I. Glasser
R. Sweke
Nicola Pancotti
Jens Eisert
J. I. Cirac
51
126
0
08 Jul 2019
Number-State Preserving Tensor Networks as Classifiers for Supervised Learning
G. Evenbly
50
11
0
15 May 2019
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