:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Li, Henry, Pereira, Marcus
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2412.16748
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Unleashing the Denoising Capability of Diffusion Prior for Solving Inverse Problems
by: Zhang, Jiawei, et al.
Published: (2024)

Solving Diffusion Inverse Problems with Restart Posterior Sampling
by: Ahmed, Bilal, et al.
Published: (2025)

Back-Projection Diffusion: Solving the Wideband Inverse Scattering Problem with Diffusion Models
by: Zhang, Borong, et al.
Published: (2024)

Constrained Particle Seeking: Solving Diffusion Inverse Problems with Just Forward Passes
by: Dou, Hongkun, et al.
Published: (2026)

Solving Inverse Problems in Protein Space Using Diffusion-Based Priors
by: Levy, Axel, et al.
Published: (2024)

Geometry-Free Conditional Diffusion Modeling for Solving the Inverse Electrocardiography Problem
by: Jara, Ramiro Valdes, et al.
Published: (2026)

Diffusion Models for Solving Inverse Problems via Posterior Sampling with Piecewise Guidance
by: Mohseni-Sehdeh, Saeed, et al.
Published: (2025)

Self-diffusion for Solving Inverse Problems
by: Luo, Guanxiong, et al.
Published: (2025)

DMPlug: A Plug-in Method for Solving Inverse Problems with Diffusion Models
by: Wang, Hengkang, et al.
Published: (2024)

Conditional Mutual Information Based Diffusion Posterior Sampling for Solving Inverse Problems
by: Hamidi, Shayan Mohajer, et al.
Published: (2025)

Warped Diffusion: Solving Video Inverse Problems with Image Diffusion Models
by: Daras, Giannis, et al.
Published: (2024)

A Gradient Flow Approach to Solving Inverse Problems with Latent Diffusion Models
by: Wang, Tim Y. J., et al.
Published: (2025)

Solving Elliptic Optimal Control Problems via Neural Networks and Optimality System
by: Dai, Yongcheng, et al.
Published: (2023)

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

Solving Video Inverse Problems Using Image Diffusion Models
by: Kwon, Taesung, et al.
Published: (2024)

Improving Diffusion Inverse Problem Solving with Decoupled Noise Annealing
by: Zhang, Bingliang, et al.
Published: (2024)

Solving the Wide-band Inverse Scattering Problem via Equivariant Neural Networks
by: Zhang, Borong, et al.
Published: (2022)

Align & Invert: Solving Inverse Problems with Diffusion and Flow-based Models via Representation Alignment
by: Sfountouris, Loukas, et al.
Published: (2025)

The Unreasonable Effectiveness of Solving Inverse Problems with Neural Networks
by: Holl, Philipp, et al.
Published: (2024)

Audio Decoding by Inverse Problem Solving
by: T., Pedro J. Villasana, et al.
Published: (2024)

Improved Physics-Driven Neural Network to Solve Inverse Scattering Problems
by: Du, Yutong, et al.
Published: (2025)

Solving the Inverse Alignment Problem for Efficient RLHF
by: Krishna, Shambhavi, et al.
Published: (2024)

Solving Linear-Gaussian Bayesian Inverse Problems with Decoupled Diffusion Sequential Monte Carlo
by: Kelvinius, Filip Ekström, et al.
Published: (2025)

Integrating Intermediate Layer Optimization and Projected Gradient Descent for Solving Inverse Problems with Diffusion Models
by: Zheng, Yang, et al.
Published: (2025)

Improving Diffusion Models for Inverse Problems Using Optimal Posterior Covariance
by: Peng, Xinyu, et al.
Published: (2024)

When To Solve, When To Verify: Compute-Optimal Problem Solving and Generative Verification for LLM Reasoning
by: Singhi, Nishad, et al.
Published: (2025)

Solving Inverse Parametrized Problems via Finite Elements and Extreme Learning Networks
by: Burman, Erik, et al.
Published: (2026)

Blind Inverse Problem Solving Made Easy by Text-to-Image Latent Diffusion
by: Dontas, Michail, et al.
Published: (2024)

Injecting Measurement Information Yields a Fast and Noise-Robust Diffusion-Based Inverse Problem Solver
by: Patsenker, Jonathan, et al.
Published: (2025)

Ambient Diffusion Posterior Sampling: Solving Inverse Problems with Diffusion Models Trained on Corrupted Data
by: Aali, Asad, et al.
Published: (2024)

Neural Optimal Design of Experiment for Inverse Problems
by: Darges, John E., et al.
Published: (2025)

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

Solving Inverse Problems via Diffusion-Based Priors: An Approximation-Free Ensemble Sampling Approach
by: Chen, Haoxuan, et al.
Published: (2025)

Solving Prior Distribution Mismatch in Diffusion Models via Optimal Transport
by: Wang, Zhanpeng, et al.
Published: (2024)

Latent Neural Operator for Solving Forward and Inverse PDE Problems
by: Wang, Tian, et al.
Published: (2024)

SILO: Solving Inverse Problems with Latent Operators
by: Raphaeli, Ron, et al.
Published: (2025)

G2D2: Gradient-Guided Discrete Diffusion for Inverse Problem Solving
by: Murata, Naoki, et al.
Published: (2024)

Repulsive Latent Score Distillation for Solving Inverse Problems
by: Zilberstein, Nicolas, et al.
Published: (2024)

Diffusion Models for Inverse Problems in the Exponential Family
by: Micheli, Alessandro, et al.
Published: (2025)

Think Twice Before You Act: Improving Inverse Problem Solving With MCMC
by: Zhu, Yaxuan, et al.
Published: (2024)