Score-Based Diffusion meets Annealed Importance Sampling

16 August 2022

Papers citing "Score-Based Diffusion meets Annealed Importance Sampling"

34 / 34 papers shown

Title
Variational Formulation of the Particle Flow Particle Filter Yinzhuang Yi Jorge Cortés Nikolay A. Atanasov 27 0 0 06 May 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
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
Learned Reference-based Diffusion Sampling for multi-modal distributions Maxence Noble Louis Grenioux Marylou Gabrié Alain Durmus DiffM 29 2 0 25 Oct 2024
Critically Damped Third-Order Langevin Dynamics Benjamin Sterling Monica Bugallo 23 0 0 12 Sep 2024
What's the score? Automated Denoising Score Matching for Nonlinear Diffusions Raghav Singhal Mark Goldstein Rajesh Ranganath DiffM 46 4 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 50 16 0 11 Jun 2024
Differentiable Annealed Importance Sampling Minimizes The Jensen-Shannon Divergence Between Initial and Target Distribution Johannes Zenn Robert Bamler 24 0 0 23 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 30 0 0 22 May 2024
Liouville Flow Importance Sampler Yifeng Tian Nishant Panda Yen Ting Lin 28 8 0 03 May 2024
DiffMOT: A Real-time Diffusion-based Multiple Object Tracker with Non-linear Prediction Weiyi Lv Yuhang Huang Ning Zhang Ruei-Sung Lin Mei Han Dan Zeng DiffM 45 16 0 04 Mar 2024
Stochastic Localization via Iterative Posterior Sampling Louis Grenioux Maxence Noble Marylou Gabrié Alain Durmus DiffM 38 12 0 16 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 32 41 0 09 Feb 2024
Ensemble-Based Annealed Importance Sampling Haoxuan Chen Lexing Ying 25 2 0 28 Jan 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
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 24 40 0 04 Oct 2023
Reparameterized Variational Rejection Sampling M. Jankowiak Du Phan DRL BDL 11 1 0 26 Sep 2023
Improved sampling via learned diffusions Lorenz Richter Julius Berner DiffM 24 52 0 03 Jul 2023
Transport meets Variational Inference: Controlled Monte Carlo Diffusions Francisco Vargas Shreyas Padhy Denis Blessing Nikolas Nusken DiffM OT 40 3 0 03 Jul 2023
Adaptive Annealed Importance Sampling with Constant Rate Progress Shirin Goshtasbpour Victor Cohen F. Pérez-Cruz 10 7 0 27 Jun 2023
Differentiating Metropolis-Hastings to Optimize Intractable Densities Gaurav Arya Ruben Seyer Frank Schafer Kartik Chandra Alexander K. Lew Mathieu Huot Vikash K. Mansinghka Jonathan Ragan-Kelley Chris Rackauckas Moritz Schauer TPM 13 4 0 13 Jun 2023
Entropy-based Training Methods for Scalable Neural Implicit Sampler Weijian Luo Boya Zhang Zhihua Zhang 21 10 0 08 Jun 2023
Efficient Training of Energy-Based Models Using Jarzynski Equality D. Carbone Mengjian Hua Simon Coste Eric Vanden-Eijnden 8 4 0 30 May 2023
To smooth a cloud or to pin it down: Guarantees and Insights on Score Matching in Denoising Diffusion Models Francisco Vargas Teodora Reu A. Kerekes Michael M Bronstein DiffM 35 1 0 16 May 2023
Resampling Gradients Vanish in Differentiable Sequential Monte Carlo Samplers Johannes Zenn Robert Bamler 27 3 0 27 Apr 2023
Improving Mutual Information Estimation with Annealed and Energy-Based Bounds Rob Brekelmans Sicong Huang Marzyeh Ghassemi Greg Ver Steeg Roger C. Grosse Alireza Makhzani 38 15 0 13 Mar 2023
Denoising Diffusion Samplers Francisco Vargas Will Grathwohl Arnaud Doucet DiffM 19 75 0 27 Feb 2023
Transport with Support: Data-Conditional Diffusion Bridges Ella Tamir Martin Trapp Arno Solin DiffM OT 23 7 0 31 Jan 2023
Proposal of a Score Based Approach to Sampling Using Monte Carlo Estimation of Score and Oracle Access to Target Density Curtis McDonald Andrew R. Barron DiffM 13 3 0 06 Dec 2022
An optimal control perspective on diffusion-based generative modeling Julius Berner Lorenz Richter Karen Ullrich DiffM 23 80 0 02 Nov 2022
Flow Annealed Importance Sampling Bootstrap Laurence Illing Midgley Vincent Stimper G. Simm Bernhard Schölkopf José Miguel Hernández-Lobato 13 77 0 03 Aug 2022
An invitation to sequential Monte Carlo samplers Chenguang Dai J. Heng Pierre E. Jacob N. Whiteley 50 65 0 23 Jul 2020