Information Perspective to Probabilistic Modeling: Boltzmann Machines versus Born Machines

Unifying neural-network quantum states and correlator product states via tensor networks

(2018) Stephen R Clark   Journal of Physics A-Mathematical and Theoretical

Mutual information, neural networks and the renormalization group

(2018) Maciej Koch-Janusz et al.   Nature Physics

Neural-Network Quantum States, String-Bond States, and Chiral Topological States

(2018) Ivan Glasser et al.   Physical Review X

Unsupervised Generative Modeling Using Matrix Product States

(2018) Zhao-Yu Han et al.   Physical Review X

Hierarchical models as marginals of hierarchical models

(2017) Guido Montúfar et al.   INTERNATIONAL JOURNAL OF APPROXIMATE REASONING

Why Does Deep and Cheap Learning Work So Well?

(2017) Henry W. Lin et al.   JOURNAL OF STATISTICAL PHYSICS

Emergence of Compositional Representations in Restricted Boltzmann Machines

(2017) J. Tubiana et al.   PHYSICAL REVIEW LETTERS

Neural Decoder for Topological Codes

(2017) Giacomo Torlai et al.   PHYSICAL REVIEW LETTERS

Solving the quantum many-body problem with artificial neural networks

(2017) Giuseppe Carleo et al.   SCIENCE

Efficient representation of quantum many-body states with deep neural networks

(2017) Xun Gao et al.   Nature Communications

Quantum Entanglement in Neural Network States

(2017) Dong-Ling Deng et al.   Physical Review X

A topological insight into restricted Boltzmann machines

(2016) Decebal Constantin Mocanu et al.   MACHINE LEARNING

Measuring the usefulness of hidden units in Boltzmann machines with mutual information

(2015) Mathias Berglund et al.   NEURAL NETWORKS

Retrieval Capabilities of Hierarchical Networks: From Dyson to Hopfield

(2015) Elena Agliari et al.   PHYSICAL REVIEW LETTERS

Critical-entanglement spectrum of one-dimensional symmetry-protected topological phases

(2014) Wen-Jia Rao et al.   PHYSICAL REVIEW B

Shannon and Rényi mutual information in quantum critical spin chains

(2014) Jean-Marie Stéphan   PHYSICAL REVIEW B

Bulk Entanglement Spectrum Reveals Quantum Criticality within a Topological State

(2014) Timothy H. Hsieh et al.   PHYSICAL REVIEW LETTERS

Extensive Parallel Processing on Scale-Free Networks

(2014) Peter Sollich et al.   PHYSICAL REVIEW LETTERS

Detecting classical phase transitions with Renyi mutual information

(2013) Jason Iaconis et al.   PHYSICAL REVIEW B

Information theoretic aspects of the two-dimensional Ising model

(2013) Hon Wai Lau et al.   PHYSICAL REVIEW E

Universal Behavior of the Shannon Mutual Information of Critical Quantum Chains

(2013) F. C. Alcaraz et al.   PHYSICAL REVIEW LETTERS

On the equivalence of Hopfield networks and Boltzmann Machines

(2012) Adriano Barra et al.   NEURAL NETWORKS

Multitasking Associative Networks

(2012) Elena Agliari et al.   PHYSICAL REVIEW LETTERS

Nature of the Spin-Liquid Ground State of theS=1/2Heisenberg Model on the Kagome Lattice

(2012) Stefan Depenbrock et al.   PHYSICAL REVIEW LETTERS

Mutual information in classical spin models

(2011) Johannes Wilms et al.   JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT

Refinements of Universal Approximation Results for Deep Belief Networks and Restricted Boltzmann Machines

(2011) Guido Montufar et al.   NEURAL COMPUTATION

Entanglement Entropy of Critical Spin Liquids

(2011) Yi Zhang et al.   PHYSICAL REVIEW LETTERS

Norm-Observable Operator Models

(2010) Ming-Jie Zhao et al.   NEURAL COMPUTATION

Measuring Renyi Entanglement Entropy in Quantum Monte Carlo Simulations

(2010) Matthew B. Hastings et al.   PHYSICAL REVIEW LETTERS

Colloquium: Area laws for the entanglement entropy

(2010) J. Eisert et al.   REVIEWS OF MODERN PHYSICS

Representational Power of Restricted Boltzmann Machines and Deep Belief Networks

(2008) Nicolas Le Roux et al.   NEURAL COMPUTATION

Area Laws in Quantum Systems: Mutual Information and Correlations

(2008) Michael M. Wolf et al.   PHYSICAL REVIEW LETTERS

Class of Quantum Many-Body States That Can Be Efficiently Simulated

(2008) G. Vidal   PHYSICAL REVIEW LETTERS