Scaling Up Machine Learning For Quantum Field Theory with Equivariant Continuous Flows

6 October 2021

Papers citing "Scaling Up Machine Learning For Quantum Field Theory with Equivariant Continuous Flows"

20 / 20 papers shown

Title
Physics-Conditioned Diffusion Models for Lattice Gauge Theory Qianteng Zhu Gert Aarts Wei Wang K. Zhou Lei Wang 58 1 0 08 Feb 2025
On learning higher-order cumulants in diffusion models Gert Aarts Diaa E. Habibi Lei Wang K. Zhou 26 4 0 28 Oct 2024
Numerical determination of the width and shape of the effective string using Stochastic Normalizing Flows M. Caselle E. Cellini A. Nada 33 4 0 24 Sep 2024
Bayesian RG Flow in Neural Network Field Theories Jessica N. Howard Marc S. Klinger Anindita Maiti A. G. Stapleton 68 1 0 27 May 2024
Multi-Lattice Sampling of Quantum Field Theories via Neural Operator-based Flows Bálint Máté Franccois Fleuret AI4CE 34 0 0 01 Jan 2024
Generative Diffusion Models for Lattice Field Theory Lei Wang Gert Aarts Kai Zhou DiffM 38 10 0 06 Nov 2023
Advances in machine-learning-based sampling motivated by lattice quantum chromodynamics Kyle Cranmer G. Kanwar S. Racanière Danilo Jimenez Rezende P. Shanahan AI4CE 29 27 0 03 Sep 2023
Sampling the lattice Nambu-Goto string using Continuous Normalizing Flows M. Caselle E. Cellini A. Nada 25 14 0 03 Jul 2023
Geometrical aspects of lattice gauge equivariant convolutional neural networks J. Aronsson David I. Müller Daniel Schuh 31 7 0 20 Mar 2023
Learning Interpolations between Boltzmann Densities Bálint Máté Franccois Fleuret 29 23 0 18 Jan 2023
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
Deformations of Boltzmann Distributions Bálint Máté Franccois Fleuret OT 28 2 0 25 Oct 2022
Amortized Bayesian Inference of GISAXS Data with Normalizing Flows Maksim Zhdanov L. Randolph T. Kluge M. Nakatsutsumi C. Gutt M. Ganeva Nico Hoffmann 34 0 0 04 Oct 2022
Path-Gradient Estimators for Continuous Normalizing Flows Lorenz Vaitl K. Nicoli Shinichi Nakajima Pan Kessel 27 13 0 17 Jun 2022
Neural Simulated Annealing Alvaro H. C. Correia Daniel E. Worrall Roberto Bondesan 19 7 0 04 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 29 19 0 10 Feb 2022
Continual Repeated Annealed Flow Transport Monte Carlo A. G. Matthews Michael Arbel Danilo Jimenez Rezende Arnaud Doucet OT 37 46 0 31 Jan 2022
Stochastic normalizing flows as non-equilibrium transformations M. Caselle E. Cellini A. Nada M. Panero 36 34 0 21 Jan 2022
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 14 13 0 22 Nov 2021
Lattice gauge symmetry in neural networks Matteo Favoni A. Ipp David I. Müller Daniel Schuh AI4CE 18 0 0 08 Nov 2021