Learning Interpolations between Boltzmann Densities

18 January 2023

Papers citing "Learning Interpolations between Boltzmann Densities"

29 / 29 papers shown

Title
Energy-based generator matching: A neural sampler for general state space Dongyeop Woo Minsu Kim Minkyu Kim Kiyoung Seong SungSoo Ahn 84 0 0 26 May 2025
Discrete Neural Flow Samplers with Locally Equivariant Transformer Zijing Ou Ruixiang Zhang Yingzhen Li 71 0 0 23 May 2025
Improving the evaluation of samplers on multi-modal targets Louis Grenioux Maxence Noble Marylou Gabrié 447 0 0 11 Apr 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 132 8 0 10 Jan 2025
Solvation Free Energies from Neural Thermodynamic Integration Bálint Máté François Fleuret Tristan Bereau 66 2 0 21 Oct 2024
NETS: A Non-Equilibrium Transport Sampler M. S. Albergo Eric Vanden-Eijnden DiffM 123 22 0 03 Oct 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 194 28 0 07 Feb 2024
Deformations of Boltzmann Distributions Bálint Máté Franccois Fleuret OT 60 2 0 25 Oct 2022
Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow Xingchao Liu Chengyue Gong Qiang Liu OOD 212 1,053 0 07 Sep 2022
Flow Annealed Importance Sampling Bootstrap Laurence Illing Midgley Vincent Stimper G. Simm Bernhard Schölkopf José Miguel Hernández-Lobato 108 95 0 03 Aug 2022
Gauge-equivariant flow models for sampling in lattice field theories with pseudofermions Ryan Abbott M. S. Albergo D. Boyda Kyle Cranmer D. Hackett ... Danilo Jimenez Rezende F. Romero-López P. Shanahan B. Tian Julian M. Urban 78 43 0 18 Jul 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 89 26 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 59 41 0 01 Jul 2022
Flow-based sampling in the lattice Schwinger model at criticality M. S. Albergo D. Boyda Kyle Cranmer D. Hackett G. Kanwar S. Racanière Danilo Jimenez Rezende F. Romero-López P. Shanahan Julian M. Urban 42 35 0 23 Feb 2022
Scaling Up Machine Learning For Quantum Field Theory with Equivariant Continuous Flows P. D. Haan Corrado Rainone Miranda C. N. Cheng Roberto Bondesan AI4CE 59 35 0 06 Oct 2021
Flow-based sampling for fermionic lattice field theories M. S. Albergo G. Kanwar S. Racanière Danilo Jimenez Rezende Julian M. Urban D. Boyda Kyle Cranmer D. Hackett P. Shanahan AI4CE 68 43 0 10 Jun 2021
Introduction to Normalizing Flows for Lattice Field Theory M. S. Albergo D. Boyda D. Hackett G. Kanwar Kyle Cranmer S. Racanière Danilo Jimenez Rezende P. Shanahan AI4CE 59 58 0 20 Jan 2021
Integrable Nonparametric Flows David Pfau Danilo Jimenez Rezende 45 5 0 03 Dec 2020
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 82 129 0 12 Aug 2020
SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows Didrik Nielsen P. Jaini Emiel Hoogeboom Ole Winther Max Welling TPM BDL DRL 63 92 0 06 Jul 2020
Array Programming with NumPy Charles R. Harris K. Millman S. Walt R. Gommers Pauli Virtanen ... Tyler Reddy Warren Weckesser Hameer Abbasi C. Gohlke T. Oliphant 156 15,026 0 18 Jun 2020
Equivariant Flows: Exact Likelihood Generative Learning for Symmetric Densities Jonas Köhler Leon Klein Frank Noé DRL 121 279 0 03 Jun 2020
Augmented Normalizing Flows: Bridging the Gap Between Generative Flows and Latent Variable Models Chin-Wei Huang Laurent Dinh Aaron Courville DRL 96 89 0 17 Feb 2020
Stochastic Normalizing Flows Hao Wu Jonas Köhler Frank Noé 136 185 0 16 Feb 2020
Generative Modeling by Estimating Gradients of the Data Distribution Yang Song Stefano Ermon SyDa DiffM 258 3,961 0 12 Jul 2019
Neural Ordinary Differential Equations T. Chen Yulia Rubanova J. Bettencourt David Duvenaud AI4CE 446 5,168 0 19 Jun 2018
Faster Eigenvector Computation via Shift-and-Invert Preconditioning Dan Garber Laurent Dinh Chi Jin Jascha Narain Sohl-Dickstein Samy Bengio Praneeth Netrapalli Aaron Sidford 277 3,722 0 26 May 2016
Variational Inference with Normalizing Flows Danilo Jimenez Rezende S. Mohamed DRL BDL 322 4,197 0 21 May 2015
Deep Unsupervised Learning using Nonequilibrium Thermodynamics Jascha Narain Sohl-Dickstein Eric A. Weiss Niru Maheswaranathan Surya Ganguli SyDa DiffM 312 7,031 0 12 Mar 2015