Reverse Diffusion Monte Carlo

5 July 2023

Tong Zhang

Papers citing "Reverse Diffusion Monte Carlo"

22 / 22 papers shown

Title
Improving the evaluation of samplers on multi-modal targets Louis Grenioux Maxence Noble Marylou Gabrié 110 0 0 11 Apr 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 74 0 0 18 Feb 2025
Inflationary Flows: Calibrated Bayesian Inference with Diffusion-Based Models Daniela de Albuquerque John Pearson DiffM 62 0 0 03 Jan 2025
Denoising Fisher Training For Neural Implicit Samplers Weijian Luo Wei Deng 36 0 0 03 Nov 2024
Learned Reference-based Diffusion Sampling for multi-modal distributions Maxence Noble Louis Grenioux Marylou Gabrié Alain Durmus DiffM 31 2 0 25 Oct 2024
Training Neural Samplers with Reverse Diffusive KL Divergence Jiajun He Wenlin Chen Mingtian Zhang David Barber José Miguel Hernández-Lobato DiffM 37 4 0 16 Oct 2024
Provable Convergence and Limitations of Geometric Tempering for Langevin Dynamics Omar Chehab Anna Korba Austin Stromme Adrien Vacher 35 2 0 13 Oct 2024
Understanding Reinforcement Learning-Based Fine-Tuning of Diffusion Models: A Tutorial and Review Masatoshi Uehara Yulai Zhao Tommaso Biancalani Sergey Levine 63 22 0 18 Jul 2024
A Practical Diffusion Path for Sampling Omar Chehab Anna Korba DiffM 34 1 0 20 Jun 2024
Model-Based Diffusion for Trajectory Optimization Chaoyi Pan Zeji Yi Guanya Shi Guannan Qu 47 6 0 28 May 2024
Accelerating Diffusion Models with Parallel Sampling: Inference at Sub-Linear Time Complexity Haoxuan Chen Yinuo Ren Lexing Ying Grant M. Rotskoff 43 15 0 24 May 2024
An Improved Analysis of Langevin Algorithms with Prior Diffusion for Non-Log-Concave Sampling Xunpeng Huang Hanze Dong Difan Zou Tong Zhang 21 0 0 10 Mar 2024
Zeroth-Order Sampling Methods for Non-Log-Concave Distributions: Alleviating Metastability by Denoising Diffusion Ye He Kevin Rojas Molei Tao DiffM 38 8 0 27 Feb 2024
Stochastic Localization via Iterative Posterior Sampling Louis Grenioux Maxence Noble Marylou Gabrié Alain Durmus DiffM 40 12 0 16 Feb 2024
Target Score Matching Valentin De Bortoli M. Hutchinson Peter Wirnsberger Arnaud Doucet DiffM 35 17 0 13 Feb 2024
Particle Denoising Diffusion Sampler Angus Phillips Hai-Dang Dau M. Hutchinson Valentin De Bortoli George Deligiannidis Arnaud Doucet DiffM 56 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 37 41 0 09 Feb 2024
Diffusive Gibbs Sampling Wenlin Chen Mingtian Zhang Brooks Paige José Miguel Hernández-Lobato David Barber 22 7 0 05 Feb 2024
Towards a Complete Analysis of Langevin Monte Carlo: Beyond Poincaré Inequality Alireza Mousavi-Hosseini Tyler Farghly Ye He Krishnakumar Balasubramanian Murat A. Erdogdu 45 25 0 07 Mar 2023
Convergence of score-based generative modeling for general data distributions Holden Lee Jianfeng Lu Yixin Tan DiffM 191 128 0 26 Sep 2022
Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions Sitan Chen Sinho Chewi Jungshian Li Yuanzhi Li Adil Salim Anru R. Zhang DiffM 135 246 0 22 Sep 2022
When is the Convergence Time of Langevin Algorithms Dimension Independent? A Composite Optimization Viewpoint Y. Freund Yi-An Ma Tong Zhang 37 16 0 05 Oct 2021