{"total":124,"rows":[{"id":"2412.13389","title":"Marigold-DC: Zero-Shot Monocular Depth Completion with Guided Diffusion","created":"2024-12-18","cited_by_count":50,"area":"diffusion"},{"id":"2412.00100","title":"Steering Rectified Flow Models in the Vector Field for Controlled Image Generation","created":"2024-11-27","cited_by_count":39,"area":"diffusion"},{"id":"2505.17004","title":"Guided Diffusion Sampling on Function Spaces with Applications to PDEs","created":"2025-05-22","cited_by_count":36,"area":"diffusion"},{"id":"2502.06805","title":"Efficient Diffusion Models: A Survey","created":"2025-02-03","cited_by_count":35,"area":"diffusion"},{"id":"2410.00418","title":"Posterior-Mean Rectified Flow: Towards Minimum MSE Photo-Realistic Image Restoration","created":"2024-10-01","cited_by_count":34,"area":"diffusion"},{"id":"2411.16443","title":"SplatFlow: Multi-View Rectified Flow Model for 3D Gaussian Splatting Synthesis","created":"2024-11-25","cited_by_count":34,"area":"diffusion"},{"id":"2504.10612","title":"Energy Matching: Unifying Flow Matching and Energy-Based Models for Generative Modeling","created":"2025-04-14","cited_by_count":27,"area":"diffusion"},{"id":"2410.04479","title":"SITCOM: Step-wise Triple-Consistent Diffusion Sampling for Inverse Problems","created":"2024-10-06","cited_by_count":24,"area":"diffusion"},{"id":"2410.16152","title":"Warped Diffusion: Solving Video Inverse Problems with Image Diffusion Models","created":"2024-10-21","cited_by_count":21,"area":"diffusion"},{"id":"2504.18720","title":"Appa: Bending Weather Dynamics with Latent Diffusion Models for Global Data Assimilation","created":"2025-04-25","cited_by_count":20,"area":"diffusion"},{"id":"2503.01161","title":"Split Gibbs Discrete Diffusion Posterior Sampling","created":"2025-03-03","cited_by_count":18,"area":"diffusion"},{"id":"2506.03979","title":"Solving Inverse Problems via Diffusion-Based Priors: An Approximation-Free Ensemble Sampling Approach","created":"2025-06-04","cited_by_count":18,"area":"diffusion"},{"id":"2508.01975","title":"Diffusion models for inverse problems","created":"2025-08-04","cited_by_count":16,"area":"diffusion"},{"id":"2410.11149","title":"Free Hunch: Denoiser Covariance Estimation for Diffusion Models Without Extra Costs","created":"2024-10-15","cited_by_count":14,"area":"diffusion"},{"id":"2411.15295","title":"Frequency-Guided Posterior Sampling for Diffusion-Based Image Restoration","created":"2024-11-22","cited_by_count":11,"area":"diffusion"},{"id":"2512.20685","title":"Diffusion Models in Simulation-Based Inference: A Tutorial Review","created":"2025-12-22","cited_by_count":11,"area":"diffusion"},{"id":"2601.23280","title":"Decoupled Diffusion Sampling for Inverse Problems on Function Spaces","created":"2026-01-30","cited_by_count":10,"area":"diffusion"},{"id":"2502.05908","title":"Inverse Problem Sampling in Latent Space Using Sequential Monte Carlo","created":"2025-02-09","cited_by_count":7,"area":"diffusion"},{"id":"2504.07437","title":"Unifying and extending Diffusion Models through PDEs for solving Inverse Problems","created":"2025-04-10","cited_by_count":7,"area":"diffusion"},{"id":"2504.17323","title":"CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors","created":"2025-04-24","cited_by_count":6,"area":"diffusion"},{"id":"2505.10311","title":"Whitened Score Diffusion: A Structured Prior for Imaging Inverse Problems","created":"2025-05-15","cited_by_count":6,"area":"diffusion"},{"id":"2507.02686","title":"Learning few-step posterior samplers by unfolding and distillation of diffusion models","created":"2025-07-03","cited_by_count":6,"area":"diffusion"},{"id":"2510.12691","title":"DiffEM: Learning from Corrupted Data with Diffusion Models via Expectation Maximization","created":"2025-10-14","cited_by_count":6,"area":"diffusion"},{"id":"2506.10955","title":"ReGuidance: A Simple Diffusion Wrapper for Boosting Sample Quality on Hard Inverse Problems","created":"2025-06-12","cited_by_count":5,"area":"diffusion"},{"id":"2512.18365","title":"Efficient Zero-Shot Inpainting with Decoupled Diffusion Guidance","created":"2025-12-20","cited_by_count":5,"area":"diffusion"},{"id":"2505.11482","title":"Unsupervised Detection of Distribution Shift in Inverse Problems using Diffusion Models","created":"2025-05-16","cited_by_count":4,"area":"diffusion"},{"id":"2506.01083","title":"Generative diffusion posterior sampling for informative likelihoods","created":"2025-06-01","cited_by_count":4,"area":"diffusion"},{"id":"2510.07206","title":"EigenScore: OOD Detection using Covariance in Diffusion Models","created":"2025-10-08","cited_by_count":4,"area":"diffusion"},{"id":"2606.12365","title":"Ambient Diffusion Policy: Imitation Learning from Suboptimal Data in Robotics","created":"2026-06-10","cited_by_count":4,"area":"diffusion"},{"id":"2607.19333","title":"Provable diffusion-based posterior sampling for linear inverse problems via DDIM","created":"2026-07-21","cited_by_count":4,"area":"diffusion"},{"id":"2501.03430","title":"A Self-supervised Diffusion Bridge for MRI Reconstruction","created":"2025-01-06","cited_by_count":3,"area":"diffusion"},{"id":"2505.11393","title":"Diff-Unfolding: A Model-Based Score Learning Framework for Inverse Problems","created":"2025-05-16","cited_by_count":3,"area":"diffusion"},{"id":"2505.17353","title":"Dual Ascent Diffusion for Inverse Problems","created":"2025-05-23","cited_by_count":3,"area":"diffusion"},{"id":"2508.00721","title":"FMPlug: Plug-In Foundation Flow-Matching Priors for Inverse Problems","created":"2025-08-01","cited_by_count":3,"area":"diffusion"},{"id":"2508.07631","title":"Efficient Approximate Posterior Sampling with Annealed Langevin Monte Carlo","created":"2025-08-11","cited_by_count":3,"area":"diffusion"},{"id":"2509.12857","title":"Bayesian Signal Separation via Plug-and-Play Diffusion-Within-Gibbs Sampling","created":"2025-09-16","cited_by_count":3,"area":"diffusion"},{"id":"2509.20511","title":"A Recovery Theory for Diffusion Priors: Deterministic Analysis of the Implicit Prior Algorithm","created":"2025-09-24","cited_by_count":3,"area":"diffusion"},{"id":"2510.23633","title":"Noise is All You Need: Solving Linear Inverse Problems by Noise Combination Sampling with Diffusion Models","created":"2025-10-24","cited_by_count":3,"area":"diffusion"},{"id":"2512.07226","title":"Unsupervised Single-Channel Audio Separation with Diffusion Source Priors","created":"2025-12-08","cited_by_count":3,"area":"diffusion"},{"id":"2604.03603","title":"Stochastic Generative Plug-and-Play Priors","created":"2026-04-04","cited_by_count":3,"area":"diffusion"},{"id":"2412.04766","title":"DAWN-FM: Data-Aware and Noise-Informed Flow Matching for Solving Inverse Problems","created":"2024-12-06","cited_by_count":2,"area":"diffusion"},{"id":"2501.15309","title":"Investigating the Feasibility of Patch-based Inference for Generalized Diffusion Priors in Inverse Problems for Medical Images","created":"2025-01-25","cited_by_count":2,"area":"diffusion"},{"id":"2503.03007","title":"Benchmarking Diffusion Annealing-Based Bayesian Inverse Problem Solvers","created":"2025-03-04","cited_by_count":2,"area":"diffusion"},{"id":"2503.22140","title":"Score-Based Turbo Message Passing for Plug-and-Play Compressive Image Recovery","created":"2025-03-28","cited_by_count":2,"area":"diffusion"},{"id":"2505.21135","title":"Learning Single Index Models with Diffusion Priors","created":"2025-05-27","cited_by_count":2,"area":"diffusion"},{"id":"2505.22090","title":"High Volume Rate 3D Ultrasound Reconstruction with Diffusion Models","created":"2025-05-28","cited_by_count":2,"area":"diffusion"},{"id":"2506.13614","title":"Exploiting the Exact Denoising Posterior Score in Training-Free Guidance of Diffusion Models","created":"2025-06-16","cited_by_count":2,"area":"diffusion"},{"id":"2507.00719","title":"Guided Unconditional and Conditional Generative Models for Super-Resolution and Inference of Quasi-Geostrophic Turbulence","created":"2025-07-01","cited_by_count":2,"area":"diffusion"},{"id":"2510.05205","title":"A Data-Driven Prism: Multi-View Source Separation with Diffusion Model Priors","created":"2025-10-06","cited_by_count":2,"area":"diffusion"},{"id":"2511.06138","title":"Latent Refinement via Flow Matching for Training-free Linear Inverse Problem Solving","created":"2025-11-08","cited_by_count":2,"area":"diffusion"},{"id":"2603.14135","title":"Conditional flow matching for physics-constrained inverse problems with finite training data","created":"2026-03-14","cited_by_count":2,"area":"diffusion"},{"id":"2604.16919","title":"Noise-Adaptive Diffusion Sampling for Inverse Problems Without Task-Specific Tuning","created":"2026-04-18","cited_by_count":2,"area":"diffusion"},{"id":"2605.06538","title":"Diffusion-Based Posterior Sampling: A Feynman-Kac Analysis of Bias and Stability","created":"2026-05-07","cited_by_count":2,"area":"diffusion"},{"id":"2605.07971","title":"DVD: Discrete Voxel Diffusion for 3D Generation and Editing","created":"2026-05-08","cited_by_count":2,"area":"diffusion"},{"id":"2605.14267","title":"Image Restoration via Diffusion Models with Dynamic Resolution","created":"2026-05-14","cited_by_count":2,"area":"diffusion"},{"id":"2411.10431","title":"Diffusion Model-based Parameter Estimation in Dynamic Power Systems","created":"2024-11-15","cited_by_count":1,"area":"diffusion"},{"id":"2501.17468","title":"Solving Inverse Problems using Diffusion with Iterative Colored Renoising","created":"2025-01-29","cited_by_count":1,"area":"diffusion"},{"id":"2502.05994","title":"Diffusion Models for Inverse Problems in the Exponential Family","created":"2025-02-09","cited_by_count":1,"area":"diffusion"},{"id":"2505.24556","title":"Predictive posterior sampling from non-stationnary Gaussian process priors via Diffusion models with application to climate data","created":"2025-05-23","cited_by_count":1,"area":"diffusion"},{"id":"2507.15809","title":"Diffusion models for multivariate subsurface generation and efficient probabilistic inversion","created":"2025-07-21","cited_by_count":1,"area":"diffusion"},{"id":"2508.16640","title":"Generative Latent Diffusion Model for Inverse Modeling and Uncertainty Analysis in Geological Carbon Sequestration","created":"2025-08-17","cited_by_count":1,"area":"diffusion"},{"id":"2509.01641","title":"Non-Identical Diffusion Models in MIMO-OFDM Channel Generation","created":"2025-09-01","cited_by_count":1,"area":"diffusion"},{"id":"2510.03352","title":"Inference-Time Search Using Side Information for Diffusion-Based Image Reconstruction","created":"2025-10-02","cited_by_count":1,"area":"diffusion"},{"id":"2510.06637","title":"Control-Augmented Autoregressive Diffusion for Data Assimilation","created":"2025-10-08","cited_by_count":1,"area":"diffusion"},{"id":"2511.08416","title":"Generative AI Meets 6G and Beyond: Diffusion Models for Semantic Communications","created":"2025-11-11","cited_by_count":1,"area":"diffusion"},{"id":"2511.12471","title":"Diffusion Model Based Signal Recovery Under 1-Bit Quantization","created":"2025-11-16","cited_by_count":1,"area":"diffusion"},{"id":"2511.20152","title":"Restora-Flow: Mask-Guided Image Restoration with Flow Matching","created":"2025-11-25","cited_by_count":1,"area":"diffusion"},{"id":"2512.17493","title":"UPMRI: Unsupervised Parallel MRI Reconstruction via Projected Conditional Flow Matching","created":"2025-12-19","cited_by_count":1,"area":"diffusion"},{"id":"2601.18932","title":"Advances in Diffusion-Based Generative Compression","created":"2026-01-26","cited_by_count":1,"area":"diffusion"},{"id":"2602.02045","title":"Outlier-robust Diffusion Posterior Sampling for Bayesian Inverse Problems","created":"2026-02-02","cited_by_count":1,"area":"diffusion"},{"id":"2602.05319","title":"Accelerated Sequential Flow Matching: A Bayesian Filtering Perspective","created":"2026-02-05","cited_by_count":1,"area":"diffusion"},{"id":"2602.07102","title":"Fast and Robust Likelihood-Guided Diffusion Posterior Sampling with Amortized Variational Inference","created":"2026-02-06","cited_by_count":1,"area":"diffusion"},{"id":"2602.07715","title":"Analyzing and Guiding Zero-Shot Posterior Sampling in Diffusion Models","created":"2026-02-07","cited_by_count":1,"area":"diffusion"},{"id":"2602.10792","title":"Bayesian Signal Component Decomposition via Diffusion-within-Gibbs Sampling","created":"2026-02-11","cited_by_count":1,"area":"diffusion"},{"id":"2608.14097","title":"Ambisonics Encoding of Room Impulse Responses using a Device-Agnostic Diffusion Model","created":"2026-08-14","cited_by_count":1,"area":"diffusion"},{"id":"2609.18466","title":"Spatially Adaptive Noise Injection","created":"2026-09-16","cited_by_count":1,"area":"diffusion"},{"id":"2505.12486","title":"Guiding Diffusion with Deep Geometric Moments: Balancing Fidelity and Variation","created":"2025-05-18","cited_by_count":0,"area":"diffusion"},{"id":"2506.13391","title":"Zero-Shot Solving of Imaging Inverse Problems via Noise-Refined Likelihood Guided Diffusion Models","created":"2025-06-16","cited_by_count":0,"area":"diffusion"},{"id":"2507.02391","title":"Posterior Transition Modeling for Unsupervised Diffusion-Based Speech Enhancement","created":"2025-07-03","cited_by_count":0,"area":"diffusion"},{"id":"2507.07008","title":"Exact Evaluation of the Accuracy of Diffusion Models for Inverse Problems with Gaussian Data Distributions","created":"2025-07-09","cited_by_count":0,"area":"diffusion"},{"id":"2508.21153","title":"WaveLLDM: Design and Development of a Lightweight Latent Diffusion Model for Speech Enhancement and Restoration","created":"2025-08-28","cited_by_count":0,"area":"diffusion"},{"id":"2509.09365","title":"Plug-and-play Diffusion Models for Image Compressive Sensing with Data Consistency Projection","created":"2025-09-11","cited_by_count":0,"area":"diffusion"},{"id":"2509.18402","title":"Measurement Score-Based MRI Reconstruction with Automatic Coil Sensitivity Estimation","created":"2025-09-22","cited_by_count":0,"area":"diffusion"},{"id":"2509.20886","title":"Nuclear Diffusion Models for Low-Rank Background Suppression in Videos","created":"2025-09-25","cited_by_count":0,"area":"diffusion"},{"id":"2509.24710","title":"MAD: Manifold Attracted Diffusion","created":"2025-09-29","cited_by_count":0,"area":"diffusion"},{"id":"2510.02208","title":"MACS: Measurement-Aware Consistency Sampling for Inverse Problems","created":"2025-10-02","cited_by_count":0,"area":"diffusion"},{"id":"2510.06335","title":"Conditional Denoising Diffusion Model-Based Robust MR Image Reconstruction from Highly Undersampled Data","created":"2025-10-07","cited_by_count":0,"area":"diffusion"},{"id":"2510.14114","title":"Briding Diffusion Posterior Sampling and Monte Carlo methods: a survey","created":"2025-10-15","cited_by_count":0,"area":"diffusion"},{"id":"2510.18291","title":"GeoDiff: Geometry-Guided Diffusion for Metric Depth Estimation","created":"2025-10-21","cited_by_count":0,"area":"diffusion"},{"id":"2511.11963","title":"Noisy MRI Reconstruction via MAP Estimation with an Implicit Deep-Denoiser Prior","created":"2025-11-15","cited_by_count":0,"area":"diffusion"},{"id":"2511.12931","title":"cryoSENSE: Compressive Sensing Enables High-throughput Microscopy with Sparse and Generative Priors on the Protein Cryo-EM Image Manifold","created":"2025-11-17","cited_by_count":0,"area":"diffusion"},{"id":"2511.16520","title":"Saving Foundation Flow-Matching Priors for Inverse Problems","created":"2025-11-20","cited_by_count":0,"area":"diffusion"},{"id":"2511.18473","title":"Uncertainty Quantification in HSI Reconstruction using Physics-Aware Diffusion Priors and Optics-Encoded Measurements","created":"2025-11-23","cited_by_count":0,"area":"diffusion"},{"id":"2512.05791","title":"Fast and Robust Diffusion Posterior Sampling for MR Image Reconstruction Using the Preconditioned Unadjusted Langevin Algorithm","created":"2025-12-05","cited_by_count":0,"area":"diffusion"},{"id":"2512.09871","title":"Diffusion Posterior Sampler for Hyperspectral Unmixing with Spectral Variability Modeling","created":"2025-12-10","cited_by_count":0,"area":"diffusion"},{"id":"2512.23232","title":"SURE Guided Posterior Sampling: Trajectory Correction for Diffusion-Based Inverse Problems","created":"2025-12-29","cited_by_count":0,"area":"diffusion"},{"id":"2601.02594","title":"Annealed Langevin Posterior Sampling (ALPS): A Rapid Algorithm for Image Restoration with Multiscale Energy Models","created":"2026-01-05","cited_by_count":0,"area":"diffusion"},{"id":"2601.23201","title":"Scale-Cascaded Diffusion Models for Super-Resolution in Medical Imaging","created":"2026-01-30","cited_by_count":0,"area":"diffusion"},{"id":"2602.00176","title":"Posterior Continuation with Noise-Conditioned Frequency Exposure for Diffusion Inverse Problems","created":"2026-01-30","cited_by_count":0,"area":"diffusion"},{"id":"2602.04189","title":"Beyond Accuracy: Evaluating Posterior Fidelity of Diffusion Inverse Solvers","created":"2026-02-04","cited_by_count":0,"area":"diffusion"}],"next_cursor":"100"}