Cover Image

Solving Inverse Problems via Diffusion-Based Priors: An Approximation-Free Ensemble Sampling Approach

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Chen, Haoxuan, Ren, Yinuo, Min, Martin Renqiang, Ying, Lexing, Izzo, Zachary
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Computer Vision and Pattern Recognition Numerical Analysis Image and Video Processing
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

How Discrete and Continuous Diffusion Meet: Comprehensive Analysis of Discrete Diffusion Models via a Stochastic Integral Framework
by: Ren, Yinuo, et al.
Published: (2024)

Accelerating Diffusion Models with Parallel Sampling: Inference at Sub-Linear Time Complexity
by: Chen, Haoxuan, et al.
Published: (2024)

Robustness and Exploration of Variational and Machine Learning Approaches to Inverse Problems: An Overview
by: Auras, Alexander, et al.
Published: (2024)

Ensemble-Based Annealed Importance Sampling
by: Chen, Haoxuan, et al.
Published: (2024)

Solving Inverse Problems with Score-Based Generative Priors learned from Noisy Data
by: Aali, Asad, et al.
Published: (2023)

Stochastic Deep Restoration Priors for Imaging Inverse Problems
by: Hu, Yuyang, et al.
Published: (2024)

Fast Inexact Bilevel Optimization for Analytical Deep Image Priors
by: Salehi, Mohammad Sadegh, et al.
Published: (2025)

FiRe: Fixed-points of Restoration Priors for Solving Inverse Problems
by: Terris, Matthieu, et al.
Published: (2024)

Enhanced Digital Halftoning via Weighted Sigma-Delta Modulation
by: Krahmer, Felix, et al.
Published: (2022)

Gaussian is All You Need: A Unified Framework for Solving Inverse Problems via Diffusion Posterior Sampling
by: Yismaw, Nebiyou, et al.
Published: (2024)

Multi Task Denoiser Training for Solving Linear Inverse Problems
by: Bled, Clément, et al.
Published: (2025)

Solving Linear Inverse Problems Using the Prior Implicit in a Denoiser
by: Kadkhodaie, Zahra, et al.
Published: (2020)

Solving Inverse Problems with FLAIR
by: Erbach, Julius, et al.
Published: (2025)

Using Randomized Nyström Preconditioners to Accelerate Variational Image Reconstruction
by: Hong, Tao, et al.
Published: (2024)

Mathematical framework for perception-driven parameter choice in image denoising
by: Isoranta, Saara, et al.
Published: (2026)

A Dual Alternating Direction Method of Multipliers for Image Decomposition and Restoration
by: Wang, Qingsong, et al.
Published: (2019)

Motion Detection in Diffraction Tomography by Common Circle Methods
by: Quellmalz, Michael, et al.
Published: (2022)

Anisotropic Diffusion Stencils: From Simple Derivations over Stability Estimates to ResNet Implementations
by: Schrader, Karl, et al.
Published: (2023)

Solving Inverse Problems by Joint Posterior Maximization with Autoencoding Prior
by: González, Mario, et al.
Published: (2021)

Trajectory Stitching for Solving Inverse Problems with Flow-Based Models
by: Denker, Alexander, et al.
Published: (2026)

Zero-Shot Solving of Imaging Inverse Problems via Noise-Refined Likelihood Guided Diffusion Models
by: Wang, Zhen, et al.
Published: (2025)

Whitened Score Diffusion: A Structured Prior for Imaging Inverse Problems
by: Alido, Jeffrey, et al.
Published: (2025)

Zero-Shot Adaptation for Approximate Posterior Sampling of Diffusion Models in Inverse Problems
by: Alçalar, Yaşar Utku, et al.
Published: (2024)

A Modular Deep Learning-based Approach for Diffuse Optical Tomography Reconstruction
by: Benfenati, Alessandro, et al.
Published: (2024)

Data-independent Low-complexity KLT Approximations for Image and Video Coding
by: Radünz, A. P., et al.
Published: (2021)

A Generative Diffusion Model to Solve Inverse Problems for Robust in-NICU Neonatal MRI
by: Arefeen, Yamin, et al.
Published: (2024)

Phase retrieval via media diversity
by: Cheng, Yan, et al.
Published: (2024)

PRISM: Probabilistic and Robust Inverse Solver with Measurement-Conditioned Diffusion Prior for Blind Inverse Problems
by: Hu, Yuanyun, et al.
Published: (2025)

Solving a Nonlinear Blind Inverse Problem for Tagged MRI with Physics and Deep Generative Priors
by: Bian, Zhangxing, et al.
Published: (2026)

Solving Inverse Problems with Flow-based Models via Model Predictive Control
by: Webber, George, et al.
Published: (2026)

Diffusion Graph Posterior Sampling for Nonlinear Inverse Problems with Application to Electrical Impedance Tomography
by: Alberti, Giovanni S., et al.
Published: (2026)

A Unified Approach to Analysis and Design of Denoising Markov Models
by: Ren, Yinuo, et al.
Published: (2025)

Multimodal Sampling via Approximate Symmetries
by: Ying, Lexing
Published: (2023)

Blaze3DM: Marry Triplane Representation with Diffusion for 3D Medical Inverse Problem Solving
by: He, Jia, et al.
Published: (2024)

Fast Data-independent KLT Approximations Based on Integer Functions
by: Radünz, A. P., et al.
Published: (2024)

Noise is All You Need: Solving Linear Inverse Problems by Noise Combination Sampling with Diffusion Models
by: Su, Xun, et al.
Published: (2025)

Diff-Unfolding: A Model-Based Score Learning Framework for Inverse Problems
by: Wang, Yuanhao, et al.
Published: (2025)

Accelerating Diffusion Models for Inverse Problems through Shortcut Sampling
by: Liu, Gongye, et al.
Published: (2023)

Occluded Face Recognition Using Low-rank Regression with Generalized Gradient Direction
by: Wu, Cho-Ying, et al.
Published: (2019)

Holographic Phase Retrieval via Wirtinger Flow: Cartesian Form with Auxiliary Amplitude
by: Uchiyama, Ittetsu, et al.
Published: (2024)