Diffusion Posterior Sampling

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Overview

Diffusion posterior sampling uses a learned generative prior and observed data to draw plausible solutions to inverse problems, where measurements may be incomplete or noisy. It is applied to tasks such as image deblurring, inpainting, CT and MRI reconstruction, and scientific problems involving physical systems. Common approaches guide reverse diffusion with likelihood gradients or data-consistency projections, while particle methods, Langevin or Gibbs sampling, and latent-space methods offer alternatives. A central challenge is making samples both faithful to the true posterior and computationally practical: approximate guidance can cause bias, poor uncertainty calibration, or hallucinations, while stronger correction can increase cost or reduce diversity.

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81 papers14 papers in the last four weeks, up 75% on the four weeks before. 0.1% of all new papers.

  1. Beyond Best-of-kk: Prior-Consistent DAPS for Ambiguous Nonlinear Inverse Problems

    Oct 22, 2026Merve Kocabas, Benjamin A. Burns, Andreas Geiger +2Diffusion-Based Inverse ProblemsInverse Problems

    University of Tübingen · Zuse School ELIZA · Max Planck Institute for Intelligent Systems +4

  2. Diffusion Posterior Sampling with Uncertain Forward Models

    Oct 21, 2026Wentao Shangguan, Vivek K GoyalDiffusion-Based Inverse ProblemsDiffusion Posterior Sampling

    Department of Electrical and Computer Engineering, Boston University, Boston, MA 02215, USA

  3. Hilbert-Scale Stability of Posterior Diffusion Priors for Ill-Posed Signal Recovery

    Oct 19, 2026Bahman Moraffah, Raha MoraffahDiffusion-Based Inverse ProblemsDiffusion Posterior Sampling

    Department of Computer Science, Data Science, and Artificial Intelligence, Worcester Polytechnic Institute

  4. Mixed Poisson diffusion models and application to posterior sampling

    Oct 14, 2026Thibaut Pellerin, Alain Durmus, Elinor Berger +1Diffusion ModelsDiffusion Posterior Sampling

    CMAP, CNRS, École polytechnique, Institut Polytechnique de Paris, Palaiseau, France · Université Paris-Saclay, CEA, List, F-91120 Palaiseau, France

  5. Spanning Diffusion and Flow-based Posterior Sampling via Exact Gaussian Conditioning

    Oct 9, 2026Teo Deveney, Lea Bogensperger, Hok Shing WongPosterior SamplingDiffusion Posterior Sampling

    University of Bath · University of Zurich · LMU Munich

  6. Kinetic Langevin Meets Split Gibbs: Accelerated Posterior Sampling for Imaging Inverse Problems with Diffusion Priors

    Oct 7, 2026Dai Hai Nguyen, Duc Dung NguyenBayesian Inverse ProblemsMarkov Chain Monte Carlo

    Hokkaido University · Institute of Information Technology, VAST

  7. Noise, Denoise, Correct: MCMC Posterior Sampling with Diffusion Priors in Three Steps

    Oct 7, 2026So Takao, Gregory David Bellchambers, Luke Ye +2Diffusion Posterior SamplingDiffusion-Based Inverse Problems

    PhysicsX London, UK

  8. Geometry-Aware Diffusion Approximate Posterior Sampling for Sparse-View and Limited-Angle CT

    Oct 5, 2026Honglei Brinkmann, Carola-Bibiane Schönlieb, Ander BiguriSparse-View CT ReconstructionComputed Tomography

    Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Cambridge, UK.

  9. Direct Intermediate Initialization for Tilted Diffusion Samplers

    Oct 5, 2026Gregory D. BellchambersPosterior SamplingDiffusion-Based Inverse Problems

    PhysicsX Ltd. London, EC2A 4DQ

  10. Frequency-Decoupled Diffusion Guidance for Non-Blind Image Deblurring

    Oct 5, 2026Sihan Wang, Jinshu Huang, Haibin Su +1Image DeblurringFrequency-Domain Image Processing

    School of Mathematical Sciences, Nankai University, Tianjin, China. · Yau Mathematical Sciences Center, Tsinghua University, Beijing, China.

  11. Measuring Effective Data Resolution in Guided Diffusion Posteriors

    Oct 3, 2026Ridham Patel, Defu Cao, Jiacheng Pang +1Diffusion-Based Inverse ProblemsDiffusion Posterior Sampling

    Indian Institute of Technology Gandhinagar Gandhinagar, India · University of Southern California Los Angeles, USA

  12. Getting Your Guidance Weights Right in diffusion and flow-matching posterior sampling

    Oct 2, 2026Liam Moroy, Jean-François Giovannelli, Yoann Altmann +3Diffusion Posterior SamplingDiffusion Guidance

    Heriot-Watt University, EPS Edinburgh, UK · IMS (Univ. Bordeaux, CNRS, BINP) Bordeaux, France · ONERA Paris, France

  13. Consecutive Posterior Fusion for Diffusive Recovery of Unobservable Image Structures

    Oct 2, 2026Elena Morotti, Davide Evangelista, Elena Loli PiccolominiDiffusion-Based Inverse ProblemsImage Inverse Problems

    Department of Computer Science and Engineerin University of Bologna Bologna, 40126, Italy

  14. SNaP: One-Step Posterior Sampling for Noisy Inverse Problems

    Sep 28, 2026Shirin Shoushtari, Edward P. Chandler, Xiao Shi +1Flow MatchingMeanFlow

    WashU · UW-Madison

  15. CLIMB-flow: Coupled Linear Inverse posterior sampling via Multiscale-Based flow

    Sep 27, 2026Zeqiu Yu, Ruizhi Yuan, Mathews JacobDiffusion Models for Image RestorationDiffusion Sampling

    Department of Electrical and Computer Engineering, University of Virginia, Charlottesville, VA, USA · Department of Biostatistics and Health Data Science, University of Pittsburgh, Pittsburgh, PA, USA

  16. Perturb-and-Solve: Efficient Learned-Operator Conditioning for Latent Diffusion Inverse Problems

    Sep 27, 2026Abduragim Shtanchaev, Arip Asadulaev, Luiza Labazanova +3Diffusion-Based Inverse ProblemsImage Restoration

    Mohamed bin Zayed University of Artificial Intelligence

  17. LoCoVSR: Local Context Diffusion Posterior Sampling for Video Super-Resolution

    Sep 26, 2026Matan Ben Chorin, Michael EladVideo Super-ResolutionVideo Restoration

    Faculty of Electrical and Computer Engineering Technion - Israel Institute of Technology Haifa, Israel · Faculty of Computer Science Department Technion - Israel Institute of Technology Haifa, Israel

  18. Learning to Replace MCMC in Split-Gibbs Diffusion Posterior Sampling via Deep Unfolding

    Sep 24, 2026Yi Zhang, Rui Guo, Mengchu Xu +2Diffusion Posterior SamplingDiffusion-Based Inverse Problems

    Faculty of Mathematics and Computer Science, Weizmann Institute of Science, Rehovot, Israel · Department of Electrical and Computer Engineering, Northeastern University, Boston, MA, USA

  19. Generative Atmospheric Super-Resolution from Heterogeneous In Situ Observations through Composable Interfaces

    Sep 24, 2026Yang Xu, Dibyajyoti Chakraborty, Haiwen Guan +2Bayesian Inverse ProblemsData Assimilation

    School of Mechanical Engineering, Purdue University, West Lafayette, Indiana, USA · College of Information Sciences and Technology, The Pennsylvania State University, University Park, Pennsylvania, USA

  20. Classification-oriented adaptive sensing via posterior sampling

    Sep 18, 2026Andriy Enttsel, Maxime Rousselot, Vincent CorlayCompressed SensingDiffusion Posterior Sampling

    Mitsubishi Electric R&D Centre Europe

  21. Direct Conditional Transition Sampling for Diffusion Inverse Problems

    Sep 13, 2026Qi Yu, Hanlin Wu, Xiaohui SunDiffusion-Based Inverse ProblemsDiffusion Posterior Sampling

    School of Information Science and Technology, Beijing Foreign Studies University

  22. Physical-State-Guided Diffusion Sampling for Full-Waveform Inversion

    Sep 11, 2026Chen Min, Haowen Jiang, Zheng Ma +1Physics-Informed Diffusion ModelsSeismic Imaging

    School of Mathematical Sciences, Shanghai Jiao Tong University, Shanghai, China · CMA-Shanghai, Shanghai Jiao Tong University, Shanghai, China · School of Mathematics and Statistics, Lanzhou University, Lanzhou, China

  23. Generative Translation Priors: Bayesian Imaging with Cross-Modality Image Translation

    Aug 28, 2026Evan Bell, Jiaming Liu, Yifan Chen +1Image ReconstructionBayesian Inverse Problems

    Johns Hopkins University · Stanford University · University of California, Los Angeles

  24. A Posterior-Dynamics Framework for Imaging Inverse Problems with Pretrained Diffusion Priors

    Aug 15, 2026Zhaoqiang Liu, Tongyao Pang, Ruibing Wang +1Diffusion Models for Image RestorationBayesian Inverse Problems

    School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China · Yau Mathematical Sciences Center, Shuangqing Complex, Tsinghua University, Beijing 100084, China

  25. RadioTrace: Transmitter-Aware Diffusion for Radio Map Estimation without Deployment-Time Fine-Tuning

    Jul 23, 2026Liu Yang, Qiang Li, Zhuo Cao +3Wireless CommunicationsDiffusion Posterior Sampling

    School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China, 611731 · School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China, 611731, and also with Tianfu Jiangxi Laboratory, Chengdu, China, 641419

  26. Strong Gravitational Lensing Posterior Sampling in Pixel-Space Using Diffusion Models and Recurrent Inference Machines

    Jul 21, 2026Guillaume Payeur, Laurence Perreault-Levasseur, Gabriel Missael Barco +1Pixel-Space Diffusion ModelsDiffusion Posterior Sampling

    Department of Physics, Universit´e de Montr´eal, Montreal QC, Canada · 2Mila - Quebec AI Institute, Montreal QC, Canada · 3Ciela Institute, Institute for Astrophysics and Machine Learning, Montreal QC, Canada +3

  27. Provable diffusion-based posterior sampling for linear inverse problems via DDIM

    Jul 21, 2026Yuchen Jiao, Na Li, Changxiao Cai +2Diffusion Models for Image RestorationBayesian Inverse Problems

    Department of Statistics and Data Science, Chinese University of Hong Kong, Hong Kong · Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor, USA · Department of Statistics and Data Science, the Wharton School, University of Pennsylvania, PA, USA

  28. Exact and Calibrated Diffusion Reconstruction for Digital Breast Tomosynthesis

    Jul 14, 2026Imade BouftiniImage ReconstructionSparse-View CT Reconstruction

  29. Joint Velocity Slope Diffusion Prior for Structurally Constrained Velocity Model Building

    Jul 6, 2026Francesco Brandolin, Tariq AlkhalifahSeismologyDiffusion Posterior Sampling

    King Abdullah University of Science and Technology (KAUST) Thuwal, Kingdom of Saudi Arabia

  30. Accelerated Likelihood Maximization for Diffusion-based Versatile Content Generation

    Jun 30, 2026Hyunsoo Lee, Inwoo Hwang, Young Min KimDiffusion SamplingDiffusion Model Acceleration

    ECE, Seoul National University · INMC & IPAI, Seoul National University