Solving Statistical Mechanics Using Variational Autoregressive Networks

27 September 2018

Lei Wang

Papers citing "Solving Statistical Mechanics Using Variational Autoregressive Networks"

50 / 79 papers shown

Title
A Generative Neural Annealer for Black-Box Combinatorial Optimization Yuan-Hang Zhang M. Di Ventra 29 0 0 14 May 2025
NeuMC -- a package for neural sampling for lattice field theories Piotr Bialas P. Korcyl T. Stebel Dawid Zapolski 39 0 0 14 Mar 2025
Hierarchical autoregressive neural networks in three-dimensional statistical system P. Białas Vaibhav Chahar P. Korcyl T. Stebel Mateusz Winiarski Dawid Zapolski 75 0 0 11 Mar 2025
Multilevel Generative Samplers for Investigating Critical Phenomena Ankur Singha E. Cellini K. Nicoli K. Jansen Stefan Kühn Shinichi Nakajima 64 1 0 11 Mar 2025
Lattice Protein Folding with Variational Annealing Shoummo Ahsan Khandoker E. Inack Mohamed Hibat-Allah AI4CE 46 0 0 28 Feb 2025
Single-Step Consistent Diffusion Samplers Pascal Jutras-Dubé Patrick Pynadath Ruqi Zhang DiffM 78 0 0 17 Feb 2025
Accurate and thermodynamically consistent hydrogen equation of state for planetary modeling with flow matching Hao Xie Saburo Howard Guglielmo Mazzola 41 1 0 17 Jan 2025
Simulating the Hubbard Model with Equivariant Normalizing Flows Dominic Schuh Janik Kreit Evan Berkowitz L. Funcke Thomas Luu K. Nicoli Marcel Rodekamp 47 3 0 13 Jan 2025
Scalable Quantum-Inspired Optimization through Dynamic Qubit Compression Co Tran Quoc-Bao Tran Hy Truong Son Thang N Dinh 33 0 0 24 Dec 2024
Machine learning the Ising transition: A comparison between discriminative and generative approaches Difei Zhang Frank Schafer Julian Arnold 70 0 0 28 Nov 2024
A theoretical perspective on mode collapse in variational inference Roman Soletskyi Marylou Gabrié Bruno Loureiro DRL 37 2 0 17 Oct 2024
A Diffusion Model Framework for Unsupervised Neural Combinatorial Optimization Sebastian Sanokowski Sepp Hochreiter Sebastian Lehner 44 17 0 03 Jun 2024
A method for quantifying the generalization capabilities of generative models for solving Ising models Qunlong Ma Zhi Ma Ming Gao 35 0 0 06 May 2024
Deep generative modelling of canonical ensemble with differentiable thermal properties Shuo-Hui Li Yao-Wen Zhang Ding Pan DRL SyDa 36 1 0 29 Apr 2024
Message Passing Variational Autoregressive Network for Solving Intractable Ising Models Qunlong Ma Zhi Ma Jinlong Xu Hairui Zhang Ming Gao 32 5 0 09 Apr 2024
CoRMF: Criticality-Ordered Recurrent Mean Field Ising Solver Zhenyu Pan Ammar Gilani En-Jui Kuo Zhuo Liu LRM 45 4 0 05 Mar 2024
Active learning of Boltzmann samplers and potential energies with quantum mechanical accuracy Ana Molina-Taborda Pilar Cossio O. Lopez-Acevedo Marylou Gabrié 30 4 0 29 Jan 2024
Variational Annealing on Graphs for Combinatorial Optimization Sebastian Sanokowski Wilhelm Berghammer Sepp Hochreiter Sebastian Lehner 56 13 0 23 Nov 2023
Generative Marginalization Models Sulin Liu Peter J. Ramadge Ryan P. Adams 39 1 0 19 Oct 2023
Diffusion Generative Flow Samplers: Improving learning signals through partial trajectory optimization Dinghuai Zhang Ricky Tian Qi Chen Cheng-Hao Liu Aaron C. Courville Yoshua Bengio 34 41 0 04 Oct 2023
Controlling Continuous Relaxation for Combinatorial Optimization Yuma Ichikawa 32 4 0 29 Sep 2023
Sampling with flows, diffusion and autoregressive neural networks: A spin-glass perspective Davide Ghio Yatin Dandi Florent Krzakala Lenka Zdeborová DiffM 30 26 0 27 Aug 2023
Training normalizing flows with computationally intensive target probability distributions P. Białas P. Korcyl T. Stebel 18 5 0 25 Aug 2023
Language models as master equation solvers Chuanbo Liu Jin Wang 41 0 0 29 Jul 2023
qecGPT: decoding Quantum Error-correcting Codes with Generative Pre-trained Transformers Han-Yu Cao Feng Pan Yijia Wang Pan Zhang AI4CE 25 7 0 18 Jul 2023
Empirical Sample Complexity of Neural Network Mixed State Reconstruction Haimeng Zhao Giuseppe Carleo F. Vicentini 36 11 0 04 Jul 2023
Balanced Training of Energy-Based Models with Adaptive Flow Sampling Louis Grenioux Eric Moulines Marylou Gabrié 26 2 0 01 Jun 2023
Compressing neural network by tensor network with exponentially fewer variational parameters Yong Qing Ke Li P. Zhou Shi-Ju Ran 22 6 0 10 May 2023
Mutual information of spin systems from autoregressive neural networks P. Białas P. Korcyl T. Stebel 32 3 0 26 Apr 2023
Locality-constrained autoregressive cum conditional normalizing flow for lattice field theory simulations R. DineshP. AI4CE 22 0 0 04 Apr 2023
The autoregressive neural network architecture of the Boltzmann distribution of pairwise interacting spins systems I. Biazzo AI4CE 34 7 0 16 Feb 2023
eVAE: Evolutionary Variational Autoencoder Zhangkai Wu LongBing Cao Lei Qi BDL DRL 33 10 0 01 Jan 2023
Simulating first-order phase transition with hierarchical autoregressive networks P. Białas Paul A. Czarnota P. Korcyl T. Stebel 9 3 0 09 Dec 2022
Aspects of scaling and scalability for flow-based sampling of lattice QCD Ryan Abbott M. S. Albergo Aleksandar Botev D. Boyda Kyle Cranmer ... Ali Razavi Danilo Jimenez Rezende F. Romero-López P. Shanahan Julian M. Urban 32 33 0 14 Nov 2022
Precision Machine Learning Eric J. Michaud Ziming Liu Max Tegmark 24 34 0 24 Oct 2022
Inference in conditioned dynamics through causality restoration Alfredo Braunstein Giovanni Catania Luca DallÁsta M. Mariani Anna Paola Muntoni 11 4 0 18 Oct 2022
Neural-network solutions to stochastic reaction networks Ying Tang Jiayu Weng Pan Zhang BDL 38 22 0 29 Sep 2022
Approximate sampling and estimation of partition functions using neural networks George T. Cantwell BDL DRL 24 1 0 21 Sep 2022
Deep Variational Free Energy Approach to Dense Hydrogen H.-j. Xie Ziqun Li Han Wang Linfeng Zhang Lei Wang 47 9 0 13 Sep 2022
Gradients should stay on Path: Better Estimators of the Reverse- and Forward KL Divergence for Normalizing Flows Lorenz Vaitl K. Nicoli Shinichi Nakajima Pan Kessel 61 24 0 17 Jul 2022
Supplementing Recurrent Neural Networks with Annealing to Solve Combinatorial Optimization Problems Shoummo Ahsan Khandoker Jawaril Munshad Abedin Mohamed Hibat-Allah 18 8 0 17 Jul 2022
An Empirical Study of Quantum Dynamics as a Ground State Problem with Neural Quantum States Vladimir Vargas-Calderón Herbert Vinck-Posada Fabio A. González 28 0 0 18 Jun 2022
Path-Gradient Estimators for Continuous Normalizing Flows Lorenz Vaitl K. Nicoli Shinichi Nakajima Pan Kessel 27 13 0 17 Jun 2022
Hierarchical autoregressive neural networks for statistical systems P. Białas P. Korcyl T. Stebel 21 11 0 21 Mar 2022
Applications of Machine Learning to Lattice Quantum Field Theory D. Boyda Salvatore Cali Sam Foreman L. Funcke D. Hackett ... Gert Aarts A. Alexandru Xiao-Yong Jin B. Lucini P. Shanahan AI4CE 32 19 0 10 Feb 2022
Estimating the Euclidean quantum propagator with deep generative modeling of Feynman paths Yanming Che C. Gneiting Franco Nori 37 6 0 06 Feb 2022
Gradient estimators for normalising flows P. Białas P. Korcyl T. Stebel BDL 24 3 0 02 Feb 2022
$$m^\ast$ of two-dimensional electron gas: a neural canonical transformation study$ $m^\ast$ of two-dimensional electron gas: a neural canonical transformation study H.-j. Xie Linfeng Zhang Lei Wang 36 8 0 10 Jan 2022
Reversible Upper Confidence Bound Algorithm to Generate Diverse Optimized Candidates Bin Chong Yingguang Yang Zi-Le Wang Hang Xing Zhirong Liu 16 4 0 30 Dec 2021
NetKet 3: Machine Learning Toolbox for Many-Body Quantum Systems F. Vicentini Damian Hofmann A. Szabó Dian Wu Christopher Roth ... Gabriel Pescia J. Nys Vladimir Vargas-Calderón N. Astrakhantsev Giuseppe Carleo 19 87 0 20 Dec 2021