Flow-based generative models for Markov chain Monte Carlo in lattice field theory

26 April 2019

Papers citing "Flow-based generative models for Markov chain Monte Carlo in lattice field theory"

36 / 36 papers shown

Title
Adjoint Sampling: Highly Scalable Diffusion Samplers via Adjoint Matching Aaron J. Havens Benjamin Kurt Miller Bing Yan Carles Domingo-Enrich Anuroop Sriram ... Brandon Amos Brian Karrer Xiang Fu Guan-Horng Liu Ricky T. Q. Chen DiffM 50 0 0 16 Apr 2025
Multilevel Generative Samplers for Investigating Critical Phenomena Ankur Singha E. Cellini K. Nicoli K. Jansen Stefan Kühn Shinichi Nakajima 62 1 0 11 Mar 2025
Single-Step Consistent Diffusion Samplers Pascal Jutras-Dubé Patrick Pynadath Ruqi Zhang DiffM 78 0 0 17 Feb 2025
From discrete-time policies to continuous-time diffusion samplers: Asymptotic equivalences and faster training Julius Berner Lorenz Richter Marcin Sendera Jarrid Rector-Brooks Nikolay Malkin OffRL 60 3 0 10 Jan 2025
On learning higher-order cumulants in diffusion models Gert Aarts Diaa E. Habibi L. Wang K. Zhou 26 4 0 28 Oct 2024
NETS: A Non-Equilibrium Transport Sampler M. S. Albergo Eric Vanden-Eijnden DiffM 47 9 0 03 Oct 2024
Neural Thermodynamic Integration: Free Energies from Energy-based Diffusion Models Bálint Máté François Fleuret Tristan Bereau DiffM 40 2 0 04 Jun 2024
Iterated Denoising Energy Matching for Sampling from Boltzmann Densities Tara Akhound-Sadegh Jarrid Rector-Brooks A. Bose Sarthak Mittal Pablo Lemos ... Siamak Ravanbakhsh Gauthier Gidel Yoshua Bengio Nikolay Malkin Alexander Tong DiffM 37 41 0 09 Feb 2024
Improved off-policy training of diffusion samplers Marcin Sendera Minsu Kim Sarthak Mittal Pablo Lemos Luca Scimeca Jarrid Rector-Brooks Alexandre Adam Yoshua Bengio Nikolay Malkin OffRL 66 17 0 07 Feb 2024
Combining Normalizing Flows and Quasi-Monte Carlo Charly Andral BDL 29 1 0 11 Jan 2024
Balanced Training of Energy-Based Models with Adaptive Flow Sampling Louis Grenioux Eric Moulines Marylou Gabrié 13 2 0 01 Jun 2023
Mutual information of spin systems from autoregressive neural networks P. Białas P. Korcyl T. Stebel 19 3 0 26 Apr 2023
Neural Diffeomorphic Non-uniform B-spline Flows S. Hong S. Chun 32 1 0 07 Apr 2023
Fluctuation without dissipation: Microcanonical Langevin Monte Carlo Jakob Robnik U. Seljak 46 6 0 31 Mar 2023
Rigid Body Flows for Sampling Molecular Crystal Structures Jonas Köhler Michele Invernizzi P. D. Haan Frank Noé AI4CE 35 27 0 26 Jan 2023
fintech-kMC: Agent based simulations of financial platforms for design and testing of machine learning systems Isaac Tamblyn Tengkai Yu Ian Benlolo 11 0 0 04 Jan 2023
Simulating 2+1D Lattice Quantum Electrodynamics at Finite Density with Neural Flow Wavefunctions Zhuo Chen Di Luo Kaiwen Hu B. Clark 27 14 0 14 Dec 2022
Toward Unlimited Self-Learning MCMC with Parallel Adaptive Annealing Yuma Ichikawa Akira Nakagawa Hiromoto Masayuki Yuhei Umeda BDL 18 0 0 25 Nov 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
Blind Super-Resolution for Remote Sensing Images via Conditional Stochastic Normalizing Flows Hanlin Wu Ning Ni Shan Wang Li-bao Zhang 35 8 0 14 Oct 2022
Deep Variational Free Energy Approach to Dense Hydrogen H.-j. Xie Ziqun Li Han Wang Linfeng Zhang Lei Wang 32 9 0 13 Sep 2022
Learning Lattice Quantum Field Theories with Equivariant Continuous Flows Mathis Gerdes P. D. Haan Corrado Rainone Roberto Bondesan Miranda C. N. Cheng AI4CE 16 40 0 01 Jul 2022
Deterministic Langevin Monte Carlo with Normalizing Flows for Bayesian Inference R. Grumitt B. Dai U. Seljak BDL 24 12 0 27 May 2022
Symmetry Group Equivariant Architectures for Physics A. Bogatskiy S. Ganguly Thomas Kipf Risi Kondor David W. Miller ... Jan T. Offermann M. Pettee P. Shanahan C. Shimmin S. Thais AI4CE 19 27 0 11 Mar 2022
A Group-Equivariant Autoencoder for Identifying Spontaneously Broken Symmetries Devanshu Agrawal A. Del Maestro Steven Johnston James Ostrowski DRL AI4CE 36 2 0 13 Feb 2022
Gradient estimators for normalising flows P. Białas P. Korcyl T. Stebel BDL 11 3 0 02 Feb 2022
Continual Repeated Annealed Flow Transport Monte Carlo A. G. Matthews Michael Arbel Danilo Jimenez Rezende Arnaud Doucet OT 34 46 0 31 Jan 2022
Stochastic normalizing flows as non-equilibrium transformations M. Caselle E. Cellini A. Nada M. Panero 22 34 0 21 Jan 2022
Machine Learning in the Search for New Fundamental Physics G. Karagiorgi Gregor Kasieczka S. Kravitz Benjamin Nachman David Shih AI4CE 42 113 0 07 Dec 2021
Latent Space Refinement for Deep Generative Models R. Winterhalder Marco Bellagente Benjamin Nachman BDL GAN DRL DiffM 10 27 0 01 Jun 2021
Sampling in Combinatorial Spaces with SurVAE Flow Augmented MCMC P. Jaini Didrik Nielsen Max Welling BDL 35 10 0 04 Feb 2021
Sampling using $SU(N)$ gauge equivariant flows D. Boyda G. Kanwar S. Racanière Danilo Jimenez Rezende M. S. Albergo Kyle Cranmer D. Hackett P. Shanahan 25 127 0 12 Aug 2020
Extending machine learning classification capabilities with histogram reweighting Dimitrios Bachtis Gert Aarts B. Lucini 14 21 0 29 Apr 2020
Stochastic Normalizing Flows Hao Wu Jonas Köhler Frank Noé 57 176 0 16 Feb 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
A Probability Density Theory for Spin-Glass Systems Gavin Hartnett Masoud Mohseni 16 3 0 03 Jan 2020