Improved sampling via learned diffusions

3 July 2023

Papers citing "Improved sampling via learned diffusions"

41 / 41 papers shown

Title
Normalize Everything: A Preconditioned Magnitude-Preserving Architecture for Diffusion-Based Speech Enhancement Julius Richter Danilo de Oliveira Timo Gerkmann DiffM 48 0 0 08 May 2025
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 43 0 0 16 Apr 2025
Improving the evaluation of samplers on multi-modal targets Louis Grenioux Maxence Noble Marylou Gabrié 47 0 0 11 Apr 2025
Underdamped Diffusion Bridges with Applications to Sampling Denis Blessing Julius Berner Lorenz Richter Gerhard Neumann DiffM 34 1 0 02 Mar 2025
End-To-End Learning of Gaussian Mixture Priors for Diffusion Sampler Denis Blessing Xiaogang Jia Gerhard Neumann DiffM 43 0 0 01 Mar 2025
Value Gradient Sampler: Sampling as Sequential Decision Making Sangwoong Yoon Himchan Hwang Hyeokju Jeong Dong Kyu Shin Che-Sang Park Sehee Kwon Frank C. Park 69 0 0 18 Feb 2025
Single-Step Consistent Diffusion Samplers Pascal Jutras-Dubé Patrick Pynadath Ruqi Zhang DiffM 73 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 56 3 0 10 Jan 2025
Inflationary Flows: Calibrated Bayesian Inference with Diffusion-Based Models Daniela de Albuquerque John Pearson DiffM 51 0 0 03 Jan 2025
Streaming Bayes GFlowNets Tiago da Silva Daniel Augusto R. M. A. de Souza Diego Mesquita BDL 28 0 0 08 Nov 2024
Learned Reference-based Diffusion Sampling for multi-modal distributions Maxence Noble Louis Grenioux Marylou Gabrié Alain Durmus DiffM 29 2 0 25 Oct 2024
Latent Abstractions in Generative Diffusion Models Giulio Franzese Mattia Martini Giulio Corallo Paolo Papotti Pietro Michiardi DiffM 31 0 0 04 Oct 2024
Implicit Dynamical Flow Fusion (IDFF) for Generative Modeling Mohammad R. Rezaei Rahul G. Krishnan Milos R. Popovic M. Lankarany DiffM 19 0 0 22 Sep 2024
Importance Corrected Neural JKO Sampling Johannes Hertrich Robert Gruhlke 26 1 0 29 Jul 2024
Dynamical Measure Transport and Neural PDE Solvers for Sampling Jingtong Sun Julius Berner Lorenz Richter Marius Zeinhofer Johannes Müller Kamyar Azizzadenesheli Anima Anandkumar OT DiffM 29 8 0 10 Jul 2024
Beyond ELBOs: A Large-Scale Evaluation of Variational Methods for Sampling Denis Blessing Xiaogang Jia Johannes Esslinger Francisco Vargas Gerhard Neumann 45 15 0 11 Jun 2024
A Diffusion Model Framework for Unsupervised Neural Combinatorial Optimization Sebastian Sanokowski Sepp Hochreiter Sebastian Lehner 27 16 0 03 Jun 2024
Amortizing intractable inference in diffusion models for vision, language, and control S. Venkatraman Moksh Jain Luca Scimeca Minsu Kim Marcin Sendera ... Alexandre Adam Jarrid Rector-Brooks Yoshua Bengio Glen Berseth Nikolay Malkin 60 24 0 31 May 2024
Stochastic Optimal Control for Diffusion Bridges in Function Spaces Byoungwoo Park Jungwon Choi Sungbin Lim Juho Lee 45 3 0 31 May 2024
Markovian Flow Matching: Accelerating MCMC with Continuous Normalizing Flows A. Cabezas Louis Sharrock Christopher Nemeth 34 1 0 23 May 2024
Control, Transport and Sampling: Towards Better Loss Design Qijia Jiang David Nabergoj OT 22 0 0 22 May 2024
Bridging discrete and continuous state spaces: Exploring the Ehrenfest process in time-continuous diffusion models Ludwig Winkler Lorenz Richter Manfred Opper 46 2 0 06 May 2024
Soft-constrained Schrodinger Bridge: a Stochastic Control Approach Jhanvi Garg Xianyang Zhang Quan Zhou DiffM OT 27 0 0 04 Mar 2024
Zeroth-Order Sampling Methods for Non-Log-Concave Distributions: Alleviating Metastability by Denoising Diffusion Ye He Kevin Rojas Molei Tao DiffM 28 8 0 27 Feb 2024
Stochastic Localization via Iterative Posterior Sampling Louis Grenioux Maxence Noble Marylou Gabrié Alain Durmus DiffM 31 11 0 16 Feb 2024
Target Score Matching Valentin De Bortoli M. Hutchinson Peter Wirnsberger Arnaud Doucet DiffM 28 17 0 13 Feb 2024
Particle Denoising Diffusion Sampler Angus Phillips Hai-Dang Dau M. Hutchinson Valentin De Bortoli George Deligiannidis Arnaud Doucet DiffM 54 25 0 09 Feb 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 27 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 62 16 0 07 Feb 2024
PQMass: Probabilistic Assessment of the Quality of Generative Models using Probability Mass Estimation Pablo Lemos Sammy N. Sharief Nikolay Malkin Laurence Perreault Levasseur Y. Hezaveh Laurence Perreault-Levasseur Yashar Hezaveh 19 3 0 06 Feb 2024
Partially Stochastic Infinitely Deep Bayesian Neural Networks Sergio Calvo-Ordoñez Matthieu Meunier Francesco Piatti Yuantao Shi BDL 35 3 0 05 Feb 2024
Denoising Diffusion Variational Inference: Diffusion Models as Expressive Variational Posteriors Wasu Top Piriyakulkij Yingheng Wang Volodymyr Kuleshov DiffM 30 1 0 05 Jan 2024
Energy based diffusion generator for efficient sampling of Boltzmann distributions Yan Wang Ling Guo Hao Wu Tao Zhou DiffM 15 3 0 04 Jan 2024
Stochastic Optimal Control Matching Carles Domingo-Enrich Jiequn Han Brandon Amos Joan Bruna Ricky T. Q. Chen DiffM 13 6 0 04 Dec 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 19 40 0 04 Oct 2023
Transport meets Variational Inference: Controlled Monte Carlo Diffusions Francisco Vargas Shreyas Padhy Denis Blessing Nikolas Nusken DiffM OT 35 3 0 03 Jul 2023
An optimal control perspective on diffusion-based generative modeling Julius Berner Lorenz Richter Karen Ullrich DiffM 20 78 0 02 Nov 2022
GFlowNets and variational inference Nikolay Malkin Salem Lahlou T. Deleu Xu Ji J. E. Hu Katie Everett Dinghuai Zhang Yoshua Bengio BDL 132 77 0 02 Oct 2022
Trajectory balance: Improved credit assignment in GFlowNets Nikolay Malkin Moksh Jain Emmanuel Bengio Chen Sun Yoshua Bengio 145 165 0 31 Jan 2022
Likelihood Training of Schrödinger Bridge using Forward-Backward SDEs Theory T. Chen Guan-Horng Liu Evangelos A. Theodorou DiffM OT 170 160 0 21 Oct 2021
VarGrad: A Low-Variance Gradient Estimator for Variational Inference Lorenz Richter Ayman Boustati Nikolas Nusken Francisco J. R. Ruiz Ömer Deniz Akyildiz DRL 124 48 0 20 Oct 2020