{"total":51,"rows":[{"id":"2410.00083","title":"A Survey on Diffusion Models for Inverse Problems","created":"2024-09-30","cited_by_count":180,"area":"diffusion"},{"id":"2405.16173","title":"Diffusion-based Reinforcement Learning via Q-weighted Variational Policy Optimization","created":"2024-05-25","cited_by_count":110,"area":"diffusion"},{"id":"2412.03142","title":"AffordDP: Generalizable Diffusion Policy with Transferable Affordance","created":"2024-12-04","cited_by_count":37,"area":"diffusion"},{"id":"2403.12404","title":"Understanding and Improving Training-free Loss-based Diffusion Guidance","created":"2024-03-19","cited_by_count":32,"area":"diffusion"},{"id":"2501.18913","title":"Rethinking Diffusion Posterior Sampling: From Conditional Score Estimator to Maximizing a Posterior","created":"2025-01-31","cited_by_count":22,"area":"diffusion"},{"id":"2508.01975","title":"Diffusion models for inverse problems","created":"2025-08-04","cited_by_count":16,"area":"diffusion"},{"id":"2403.18636","title":"A Diffusion-Based Generative Equalizer for Music Restoration","created":"2024-03-27","cited_by_count":12,"area":"diffusion"},{"id":"2405.14677","title":"RectifID: Personalizing Rectified Flow with Anchored Classifier Guidance","created":"2024-05-23","cited_by_count":11,"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":"2505.05853","title":"PICD: Versatile Perceptual Image Compression with Diffusion Rendering","created":"2025-05-09","cited_by_count":11,"area":"diffusion"},{"id":"2411.10932","title":"Constrained Diffusion with Trust Sampling","created":"2024-11-17","cited_by_count":10,"area":"diffusion"},{"id":"2407.11288","title":"Zero-Shot Adaptation for Approximate Posterior Sampling of Diffusion Models in Inverse Problems","created":"2024-07-16","cited_by_count":9,"area":"diffusion"},{"id":"2506.00867","title":"Local Manifold Approximation and Projection for Manifold-Aware Diffusion Planning","created":"2025-06-01","cited_by_count":9,"area":"diffusion"},{"id":"2403.12063","title":"Consistency Model is an Effective Posterior Sample Approximation for Diffusion Inverse Solvers","created":"2024-02-09","cited_by_count":8,"area":"diffusion"},{"id":"2503.16973","title":"ARFlow: Human Action-Reaction Flow Matching with Physical Guidance","created":"2025-03-21","cited_by_count":7,"area":"diffusion"},{"id":"2411.07625","title":"Flow Matching Posterior Sampling: A Training-free Conditional Generation for Flow Matching","created":"2024-11-12","cited_by_count":4,"area":"diffusion"},{"id":"2508.06266","title":"ADPro: a Test-time Adaptive Diffusion Policy via Manifold-constrained Denoising and Task-aware Initialization for Robotic Manipulation","created":"2025-08-08","cited_by_count":4,"area":"diffusion"},{"id":"2601.22443","title":"Weak Diffusion Priors Can Still Achieve Strong Inverse-Problem Performance","created":"2026-01-30","cited_by_count":4,"area":"diffusion"},{"id":"2411.16216","title":"SMGDiff: Soccer Motion Generation using diffusion probabilistic models","created":"2024-11-25","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":"2509.11724","title":"DRAG: Data Reconstruction Attack using Guided Diffusion","created":"2025-09-15","cited_by_count":3,"area":"diffusion"},{"id":"2509.24531","title":"Diffusion Bridge or Flow Matching? A Unifying Framework and Comparative Analysis","created":"2025-09-29","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":"2404.11416","title":"Neural Shr\\\"odinger Bridge Matching for Pansharpening","created":"2024-04-17","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":"2510.07343","title":"Local MAP Sampling for Diffusion Models","created":"2025-10-07","cited_by_count":2,"area":"diffusion"},{"id":"2602.11850","title":"Free Lunch for Stabilizing Rectified Flow Inversion","created":"2026-02-12","cited_by_count":2,"area":"diffusion"},{"id":"2603.02646","title":"Compositional Visual Planning via Inference-Time Diffusion Scaling","created":"2026-03-03","cited_by_count":2,"area":"diffusion"},{"id":"2404.03706","title":"Bi-level Guided Diffusion Models for Zero-Shot Medical Imaging Inverse Problems","created":"2024-04-04","cited_by_count":1,"area":"diffusion"},{"id":"2404.18252","title":"Improving Training-free Conditional Diffusion Model via Fisher Information","created":"2024-04-28","cited_by_count":1,"area":"diffusion"},{"id":"2411.00359","title":"Linearly Constrained Diffusion Implicit Models","created":"2024-11-01","cited_by_count":1,"area":"diffusion"},{"id":"2411.03053","title":"Gradient-Guided Conditional Diffusion Models for Private Image Reconstruction: Analyzing Adversarial Impacts of Differential Privacy and Denoising","created":"2024-11-05","cited_by_count":1,"area":"diffusion"},{"id":"2501.15128","title":"MAP-based Problem-Agnostic diffusion model for Inverse Problems","created":"2025-01-25","cited_by_count":1,"area":"diffusion"},{"id":"2506.11893","title":"Measurement-Aligned Sampling for Inverse Problem","created":"2025-06-13","cited_by_count":1,"area":"diffusion"},{"id":"2511.10423","title":"Enhanced Privacy Leakage from Noise-Perturbed Gradients via Gradient-Guided Conditional Diffusion Models","created":"2025-11-13","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":"2605.30056","title":"Sample-Efficient Diffusion-based Reinforcement Learning with Critic Guidance","created":"2026-05-28","cited_by_count":1,"area":"diffusion"},{"id":"2606.28417","title":"DiffRGD: An Inference-Time Diffusion Guidance Through Riemannian Gradient Descent","created":"2026-06-25","cited_by_count":1,"area":"diffusion"},{"id":"2607.17972","title":"DiFA: Inference-Time Forward-Process Alignment for Diffusion Models","created":"2026-07-20","cited_by_count":1,"area":"diffusion"},{"id":"2509.24395","title":"Unsupervised Single-Channel Speech Separation with Diffusion under Speaker-Embedding Guidance","created":"2025-09-29","cited_by_count":0,"area":"diffusion"},{"id":"2510.02043","title":"Zero-shot Human Pose Estimation using Diffusion-based Inverse solvers","created":"2025-10-02","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":"2511.18471","title":"Jacobian-Aware Posterior Sampling for Inverse Problems","created":"2025-11-23","cited_by_count":0,"area":"diffusion"},{"id":"2602.23214","title":"Plug-and-Play Diffusion Meets ADMM: Dual-Variable Coupling for Robust Medical Image Reconstruction","created":"2026-02-26","cited_by_count":0,"area":"diffusion"},{"id":"2605.29937","title":"Fisher-Preserving Guidance: Training-Free Manifold Constraints for Safe Diffusion Control","created":"2026-05-28","cited_by_count":0,"area":"diffusion"},{"id":"2607.14398","title":"Integration Matters: Rollout-Based Training for Constrained Diffusion Models","created":"2026-07-15","cited_by_count":0,"area":"diffusion"},{"id":"2608.05103","title":"Multimodal Spatiotemporal Atmospheric Data Assimilation with Latent Video Flow-matching","created":"2026-08-05","cited_by_count":0,"area":"diffusion"},{"id":"2609.35944","title":"EnJoi: Ensemble Joint Score Filter for Generative Data Assimilation","created":"2026-09-28","cited_by_count":0,"area":"diffusion"},{"id":"2610.04538","title":"FASTER: Fast Adjoint Stochastic Transport for Endpoint Refinement in Reward-Guided Image Editing","created":"2026-10-03","cited_by_count":0,"area":"diffusion"},{"id":"2610.06221","title":"Frequency-Decoupled Diffusion Guidance for Non-Blind Image Deblurring","created":"2026-10-05","cited_by_count":0,"area":"diffusion"}],"next_cursor":null}