Sampling using $SU(N)$ gauge equivariant flows

12 August 2020

D. Boyda

G. Kanwar

S. Racanière

Danilo Jimenez Rezende

Papers citing "Sampling using $SU(N)$ gauge equivariant flows"

50 / 66 papers shown

Title
Learning Chern Numbers of Topological Insulators with Gauge Equivariant Neural Networks Longde Huang Oleksandr Balabanov H. Linander Mats Granath Daniel Persson Jan E. Gerken 34 0 0 24 Feb 2025
Physics-Conditioned Diffusion Models for Lattice Gauge Theory Qianteng Zhu Gert Aarts Wei Wang K. Zhou L. Wang 53 1 0 08 Feb 2025
MatrixNet: Learning over symmetry groups using learned group representations Lucas Laird Circe Hsu Asilata Bapat Robin Walters AI4CE 43 0 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 34 3 0 13 Jan 2025
Does equivariance matter at scale? Johann Brehmer S. Behrends P. D. Haan Taco S. Cohen 44 10 0 30 Oct 2024
Improving Equivariant Model Training via Constraint Relaxation Stefanos Pertigkiozoglou Evangelos Chatzipantazis Shubhendu Trivedi Kostas Daniilidis 39 4 0 23 Aug 2024
TASI Lectures on Physics for Machine Learning Jim Halverson 28 1 0 31 Jul 2024
Neural Approximate Mirror Maps for Constrained Diffusion Models Berthy T. Feng Ricardo Baptista Katherine L. Bouman MedIm DiffM 40 3 0 18 Jun 2024
Machine learning a fixed point action for SU(3) gauge theory with a gauge equivariant convolutional neural network Kieran Holland A. Ipp David I. Müller Urs Wenger AI4CE 11 6 0 12 Jan 2024
Energy based diffusion generator for efficient sampling of Boltzmann distributions Yan Wang Ling Guo Hao Wu Tao Zhou DiffM 34 3 0 04 Jan 2024
Multi-Lattice Sampling of Quantum Field Theories via Neural Operator-based Flows Bálint Máté Franccois Fleuret AI4CE 26 0 0 01 Jan 2024
Learning Distributions on Manifolds with Free-form Flows Peter Sorrenson Felix Dräxler Armand Rousselot Sander Hummerich Ullrich Kothe DRL AI4CE 24 2 0 15 Dec 2023
$$\mathbb{Z}_2\times \mathbb{Z}_2$ Equivariant Quantum Neural Networks: Benchmarking against Classical Neural Networks$ $\mathbb{Z}_2\times \mathbb{Z}_2$ Equivariant Quantum Neural Networks: Benchmarking against Classical Neural Networks Zhongtian Dong Marçal Comajoan Cara Gopal Ramesh Dahale Roy T. Forestano S. Gleyzer ... Kyoungchul Kong Tom Magorsch Konstantin T. Matchev Katia Matcheva Eyup B. Unlu 20 5 0 30 Nov 2023
Scaling Riemannian Diffusion Models Aaron Lou Minkai Xu Stefano Ermon 22 8 0 30 Oct 2023
Generative Modeling on Manifolds Through Mixture of Riemannian Diffusion Processes Jaehyeong Jo Sung Ju Hwang DiffM 29 9 0 11 Oct 2023
SE(3)-Stochastic Flow Matching for Protein Backbone Generation A. Bose Tara Akhound-Sadegh Guillaume Huguet Kilian Fatras Jarrid Rector-Brooks Cheng-Hao Liu A. Nica Maksym Korablyov Michael M. Bronstein Alexander Tong DiffM 39 72 0 03 Oct 2023
Accelerating Markov Chain Monte Carlo sampling with diffusion models N. Hunt-Smith W. Melnitchouk F. Ringer Nobuo Sato A. Thomas M. J. White DiffM 18 15 0 04 Sep 2023
Advances in machine-learning-based sampling motivated by lattice quantum chromodynamics Kyle Cranmer G. Kanwar S. Racanière Danilo Jimenez Rezende P. Shanahan AI4CE 20 27 0 03 Sep 2023
Sampling the lattice Nambu-Goto string using Continuous Normalizing Flows M. Caselle E. Cellini A. Nada 18 14 0 03 Jul 2023
Understanding Deep Generative Models with Generalized Empirical Likelihoods Suman V. Ravuri Mélanie Rey S. Mohamed M. Deisenroth VLM 19 5 0 16 Jun 2023
Spontaneous Symmetry Breaking in Generative Diffusion Models G. Raya L. Ambrogioni DiffM 17 30 0 31 May 2023
Statistical Guarantees of Group-Invariant GANs Ziyu Chen M. Katsoulakis Luc Rey-Bellet Wei-wei Zhu 36 2 0 22 May 2023
Gauge-equivariant pooling layers for preconditioners in lattice QCD C. Lehner T. Wettig AI4CE 17 8 0 20 Apr 2023
Neural Diffeomorphic Non-uniform B-spline Flows S. Hong S. Chun 32 1 0 07 Apr 2023
Locality-constrained autoregressive cum conditional normalizing flow for lattice field theory simulations R. DineshP. AI4CE 17 0 0 04 Apr 2023
EDGI: Equivariant Diffusion for Planning with Embodied Agents Johann Brehmer Joey Bose P. D. Haan Taco S. Cohen DiffM 23 32 0 22 Mar 2023
Geometrical aspects of lattice gauge equivariant convolutional neural networks J. Aronsson David I. Müller Daniel Schuh 20 7 0 20 Mar 2023
Gauge-equivariant neural networks as preconditioners in lattice QCD C. Lehner T. Wettig AI4CE 12 9 0 10 Feb 2023
Sample Complexity of Probability Divergences under Group Symmetry Ziyu Chen M. Katsoulakis Luc Rey-Bellet Weixia Zhu 20 10 0 03 Feb 2023
Rigid Body Flows for Sampling Molecular Crystal Structures Jonas Köhler Michele Invernizzi P. D. Haan Frank Noé AI4CE 32 27 0 26 Jan 2023
Learning Interpolations between Boltzmann Densities Bálint Máté Franccois Fleuret 22 23 0 18 Jan 2023
Simulating 2+1D Lattice Quantum Electrodynamics at Finite Density with Neural Flow Wavefunctions Zhuo Chen Di Luo Kaiwen Hu B. Clark 19 14 0 14 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 26 33 0 14 Nov 2022
Gauge Equivariant Neural Networks for 2+1D U(1) Gauge Theory Simulations in Hamiltonian Formulation Di Luo Shunyue Yuan J. Stokes B. Clark 21 14 0 06 Nov 2022
Grassmann Manifold Flows for Stable Shape Generation Ryoma Yataka Kazuki Hirashima Masashi Shiraishi 19 1 0 05 Nov 2022
Deformations of Boltzmann Distributions Bálint Máté Franccois Fleuret OT 20 2 0 25 Oct 2022
Theoretical Guarantees for Permutation-Equivariant Quantum Neural Networks Louis Schatzki Martín Larocca Quynh T. Nguyen F. Sauvage M. Cerezo 27 84 0 18 Oct 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 48 24 0 17 Jul 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
Simulator-Based Inference with Waldo: Confidence Regions by Leveraging Prediction Algorithms and Posterior Estimators for Inverse Problems Luca Masserano T. Dorigo Rafael Izbicki Mikael Kuusela Ann B. Lee 11 11 0 31 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
Unsupervised Learning of Group Invariant and Equivariant Representations R. Winter Marco Bertolini Tuan Le Frank Noé Djork-Arné Clevert 23 40 0 15 Feb 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 24 19 0 10 Feb 2022
Structure-preserving GANs Jeremiah Birrell M. Katsoulakis Luc Rey-Bellet Wei-wei Zhu GAN 13 18 0 02 Feb 2022
Stochastic normalizing flows as non-equilibrium transformations M. Caselle E. Cellini A. Nada M. Panero 12 34 0 21 Jan 2022
Machine Learning Trivializing Maps: A First Step Towards Understanding How Flow-Based Samplers Scale Up L. Debbio Joe Marsh Rossney Michael Wilson 11 6 0 31 Dec 2021
Preserving gauge invariance in neural networks Matteo Favoni A. Ipp David I. Müller Daniel Schuh 11 1 0 21 Dec 2021
Machine Learning in Nuclear Physics A. Boehnlein M. Diefenthaler C. Fanelli M. Hjorth-Jensen T. Horn ... M. Schram A. Scheinker Michael S. Smith Xin-Nian Wang Veronique Ziegler AI4CE 29 41 0 04 Dec 2021
Group equivariant neural posterior estimation Maximilian Dax Stephen R. Green J. Gair Michael Deistler Bernhard Schölkopf Jakob H. Macke BDL 33 31 0 25 Nov 2021
Lattice gauge symmetry in neural networks Matteo Favoni A. Ipp David I. Müller Daniel Schuh AI4CE 16 0 0 08 Nov 2021

Sampling using SU(N)SU(N)SU(N) gauge equivariant flows

Papers citing "Sampling using $SU(N)$ gauge equivariant flows"

Sampling using $SU(N)$ gauge equivariant flows