Solving Statistical Mechanics Using Variational Autoregressive Networks

27 September 2018

Lei Wang

Papers citing "Solving Statistical Mechanics Using Variational Autoregressive Networks"

29 / 79 papers shown

Title
Machine Learning of Thermodynamic Observables in the Presence of Mode Collapse K. Nicoli Christopher J. Anders L. Funcke T. Hartung K. Jansen Pan Kessel Shinichi Nakajima Paolo Stornati AI4CE 33 13 0 22 Nov 2021
Analysis of autocorrelation times in Neural Markov Chain Monte Carlo simulations P. Białas P. Korcyl T. Stebel 17 9 0 19 Nov 2021
A Bayesian generative neural network framework for epidemic inference problems I. Biazzo Alfredo Braunstein Luca DallÁsta Fabio Mazza 24 16 0 05 Nov 2021
Local-Global MCMC kernels: the best of both worlds S. Samsonov E. Lagutin Marylou Gabrié Alain Durmus A. Naumov Eric Moulines 19 13 0 04 Nov 2021
Efficient Bayesian Sampling Using Normalizing Flows to Assist Markov Chain Monte Carlo Methods Marylou Gabrié Grant M. Rotskoff Eric Vanden-Eijnden 19 18 0 16 Jul 2021
Overcoming barriers to scalability in variational quantum Monte Carlo Tianchen Zhao Saibal De Brian Chen J. Stokes S. Veerapaneni BDL DRL 16 11 0 24 Jun 2021
Tensor networks for unsupervised machine learning Jing Liu Sujie Li Jiang Zhang Pan Zhang SSL 25 25 0 24 Jun 2021
Ab-initio study of interacting fermions at finite temperature with neural canonical transformation Hao Xie Linfeng Zhang Lei Wang 20 26 0 18 May 2021
Unbiased Monte Carlo Cluster Updates with Autoregressive Neural Networks Dian Wu R. Rossi Giuseppe Carleo 32 29 0 12 May 2021
Scaling of neural-network quantum states for time evolution Sheng-Hsuan Lin F. Pollmann 21 25 0 21 Apr 2021
Variational Autoencoder Analysis of Ising Model Statistical Distributions and Phase Transitions D. Yevick DRL 14 7 0 13 Apr 2021
Variational Neural Annealing Mohamed Hibat-Allah E. Inack R. Wiersema R. Melko Juan Carrasquilla DRL 19 80 0 25 Jan 2021
Noise-Robust End-to-End Quantum Control using Deep Autoregressive Policy Networks Jiahao Yao Paul Köttering Hans Gundlach Lin Lin Marin Bukov 26 14 0 12 Dec 2020
Reconstruction of Pairwise Interactions using Energy-Based Models Christoph Feinauer C. Lucibello 14 4 0 11 Dec 2020
Reinforcement Learning for Many-Body Ground-State Preparation Inspired by Counterdiabatic Driving Jiahao Yao Lin Lin Marin Bukov BDL AI4CE 32 61 0 07 Oct 2020
Estimation of Thermodynamic Observables in Lattice Field Theories with Deep Generative Models K. Nicoli Christopher J. Anders L. Funcke T. Hartung K. Jansen Pan Kessel Shinichi Nakajima Paolo Stornati AI4CE 8 3 0 14 Jul 2020
Extending machine learning classification capabilities with histogram reweighting Dimitrios Bachtis Gert Aarts B. Lucini 19 21 0 29 Apr 2020
A Perspective on Deep Learning for Molecular Modeling and Simulations Jun Zhang Yao-Kun Lei Zhen Zhang Junhan Chang Maodong Li Xu Han Lijiang Yang Yue Yang Y. Gao AI4CE 37 8 0 25 Apr 2020
Deep Deterministic Portfolio Optimization Ayman Chaouki Stephen J. Hardiman Christian Schmidt Emmanuel Sérié J. D. Lataillade 12 18 0 13 Mar 2020
Watch and learn -- a generalized approach for transferrable learning in deep neural networks via physical principles Kyle Sprague Juan Carrasquilla S. Whitelam Isaac Tamblyn FedML AI4CE OOD 19 5 0 03 Mar 2020
Towards Novel Insights in Lattice Field Theory with Explainable Machine Learning Stefan Blücher Lukas Kades J. Pawlowski Nils Strodthoff Julian M. Urban AI4CE 9 32 0 03 Mar 2020
Targeted free energy estimation via learned mappings Peter Wirnsberger A. J. Ballard George Papamakarios Stuart Abercrombie S. Racanière Alexander Pritzel Danilo Jimenez Rezende Charles Blundell 27 86 0 12 Feb 2020
Quantum-inspired annealers as Boltzmann generators for machine learning and statistical physics Alexander Ulanov E. Tiunov A. Lvovsky AI4CE 8 7 0 18 Dec 2019
Neural Canonical Transformation with Symplectic Flows Shuo-Hui Li Chen Dong Linfeng Zhang Lei Wang DRL 34 28 0 30 Sep 2019
Towards Explainable Artificial Intelligence Wojciech Samek K. Müller XAI 32 437 0 26 Sep 2019
Inverse Ising inference from high-temperature re-weighting of observations Junghyo Jo Danh-Tai Hoang V. Periwal 11 0 0 10 Sep 2019
Compressing deep neural networks by matrix product operators Ze-Feng Gao Song Cheng Rong-Qiang He Z. Xie Hui-Hai Zhao Zhong-Yi Lu Tao Xiang 23 39 0 11 Apr 2019
Deep autoregressive models for the efficient variational simulation of many-body quantum systems Or Sharir Yoav Levine Noam Wies Giuseppe Carleo Amnon Shashua 24 187 0 11 Feb 2019
Geometric deep learning: going beyond Euclidean data M. Bronstein Joan Bruna Yann LeCun Arthur Szlam P. Vandergheynst GNN 264 3,243 0 24 Nov 2016