Diffusion Model Sampling

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5 papers in the last four weeks, with none the four weeks before. 0.0% of all new papers.

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Self-supervised Dynamic Heterogeneous Degradation Modeling for Unified Zero-Shot Image Restoration
May 23, 2026XiaoWan Hu, Jing Yang, HeNan Liu +2Diffusion Models for Image Restoration Diffusion Model Sampling
Beihang University · Tsinghua University
Uniform Diffusion Models Revisited: Leave-One-Out Denoiser and Absorbing State Reformulation
May 21, 2026Samson Gourevitch, Yazid Janati, Dario Shariatian +4Diffusion Model Sampling Diffusion Language Models
CMAP, Ecole polytechnique · Institute of Foundation Models · Inria, PSL Research University +2
The Value of Covariance Matching in Gaussian DDPMs and the Lanczos Sampler
May 21, 2026Md Sahil Akhtar, Aymane El Gadarri, Vivek F. Farias +1Diffusion Model Sampling Distribution Matching
Electrical Engineering and Computer Science · Massachusetts Institute of Technology · Operations Research Center +1
A Tutorial on Diffusion Theory: From Differential Equations to Diffusion Models
May 21, 2026Jiayi Fu, Yuxia WangDiffusion Model Sampling Score-Based Generative Modeling
INSAIT, Sofia University “St. Kliment Ohridski”, Bulgaria
Semantic Granularity Navigation in Image Editing
May 20, 2026Liangsi Lu, Minzhe Guo, Xuhang Chen +1Diffusion Model Sampling Diffusion Timestep Scheduling
Guangdong University of Technology, Guangzhou, China · Huizhou University, Huizhou, China.
Generative Pseudo-Force Fields for Molecular Generation
May 18, 2026Stefaan Simon Pierre Hessmann, Khaled Kahouli, Stefan Gugler +4Machine Learning Interatomic Potentials Diffusion Model Sampling
Machine Learning Group, Technische Universität Berlin, Berlin, Germany · BIFOLD – Berlin Institute for the Foundations of Learning and Data, Berlin, Germany · Department of Mathematics and Computer Science, Freie Universität Berlin, Berlin, Germany +6
Do Heavy Tails Help Diffusion? On the Subtle Trade-off Between Initialization and Training
May 13, 2026Hamza Cherkaoui, Hélène Halconruy, Antonio OcelloDiffusion Model Sampling Heavy-Tailed Noise
SAMOVAR, Télécom SudParis, Institut Polytechnique de Paris, Palaiseau, France · Modal’X, Université Paris Nanterre, Nanterre, France · CREST, ENSAE Paris, Institut Polytechnique de Paris, Palaiseau, France
Covariance-aware sampling for Diffusion Models
May 13, 2026Andrea Schioppa, Tim SalimansDiffusion Model Sampling Diffusion Sampling
GDM - Amsterdam · work done at GDM - Amsterdam
Generative Motion In-betweening by Diffusion over Continuous Implicit Representations
May 12, 2026Shiyu Fan, Paul Henderson, Edmond S. L. HoImplicit Neural Representations Latent Diffusion Models
School of Computing Science, University of Glasgow, United Kingdom.
MoCam: Unified Novel View Synthesis via Structured Denoising Dynamics
May 12, 2026Haofeng Liu, Yang Zhou, Ziheng Wang +6Diffusion Model Sampling Dynamic Novel View Synthesis
Tempered Guided Diffusion
May 5, 2026Andreas Makris, Paul Fearnhead, Chris NemethDiffusion Model Sampling Diffusion-Based Inverse Problems
Department of Mathematics and Statistics Lancaster University, UK · Department of Mathematics and Statistics2026 Lancaster University, UK
Delta Score Matters! Spatial Adaptive Multi Guidance in Diffusion Models
Apr 29, 2026Haosen Li, Wenshuo Chen, Lei Wang +4Diffusion Model Guidance Classifier-Free Guidance
1The Hong Kong University of Science and Technology (Guangzhou) · 2Griffith University & Data61/CSIRO
Exploring Time Conditioning in Diffusion Generative Models from Disjoint Noisy Data Manifolds
Apr 28, 2026Liuzhuozheng Li, Zhiyuan Zhan, Shuhong Liu +5Diffusion Model Sampling Conditional Diffusion Models
SGIT AI Lab · UTokyo · RIKEN AIP +4
Denoising, Fast and Slow: Difficulty-Aware Adaptive Sampling for Image Generation
Apr 21, 2026Johannes Schusterbauer, Ming Gui, Yusong Li +3Diffusion Model Sampling Diffusion Sampling
Efficient Diffusion Models under Nonconvex Equality and Inequality constraints via Landing
Apr 20, 2026Kijung Jeon, Michael Muehlebach, Molei TaoConstrained Generative Modeling Langevin Dynamics
Georgia Institute of Technology · Max Planck Institute for Int. Sys.
Interpolating Discrete Diffusion Models with Controllable Resampling
Apr 19, 2026Marcel Kollovieh, Sirine Ayadi, Stephan GünnemannDiffusion Model Sampling Molecular Graph Generation
School of Computation, Information and Technology, Technical University of Munich
Elucidating the SNR-t Bias of Diffusion Probabilistic Models
Apr 17, 2026Meng Yu, Lei Sun, Jianhao Zeng +2Diffusion Model Sampling Diffusion Sampling
Lanzhou University · AMAP Alibaba Group
Q-Drift: Quantization-Aware Drift Correction for Diffusion Model Sampling
Mar 18, 2026Sooyoung Ryu, Mathieu Salzmann, Saqib JavedDiffusion Model Quantization Diffusion Model Sampling
Department of Computer Science and Engineering, Seoul National University, Seoul, South Korea · School of Computer and Communication Sciences, EPFL, Lausanne, Switzerland · Meta Reality Labs, Redmond, USA
Trust-Region Noise Search for Black-Box Alignment of Diffusion and Flow Models
Mar 15, 2026Niklas Schweiger, Daniel Cremers, Karnik RamDiffusion Model Alignment Black-Box Optimization
Technical University of Munich, Germany · Munich Center for Machine Learning, Germany
Efficient Generative Modeling beyond Memoryless Diffusion via Adjoint Schrödinger Bridge Matching
Feb 17, 2026Jeongwoo Shin, Jinhwan Sul, Joonseok Lee +2Diffusion Model Sampling Schrödinger Bridges
Seoul National University, Seoul, Korea · Georgia Institute of Technology, Atlanta, GA, USA · Sungkyunkwan University, Seoul, Korea
Efficient Sampling with Discrete Diffusion Models: Sharp and Adaptive Guarantees
Feb 16, 2026Daniil Dmitriev, Zhihan Huang, Yuting WeiSample Complexity Diffusion Model Sampling
Department of Statistics and Data Science, the Wharton School, University of Pennsylvania
Formalizing the Sampling Design Space of Diffusion-Based Generative Models via Adaptive Solvers and Wasserstein-Bounded Timesteps
Feb 13, 2026Sangwoo Jo, Sungjoon ChoiDiffusion Model Sampling Diffusion Sampling
Department of Artificial Intelligence, Korea University, Seoul, South Korea.
A Random Matrix Theory Perspective on the Consistency of Diffusion Models
Feb 2, 2026Binxu Wang, Jacob Zavatone-Veth, Cengiz PehlevanDiffusion Model Sampling ML Reproducibility
Kempner Institute, Harvard University, Boston, MA, USA · Center for Brain Science, Harvard University, Cambridge, MA, USA · Society of Fellows, Harvard University, Cambridge, MA, USA +1
Control Variate Score Matching for Diffusion Models
Dec 23, 2025Khaled Kahouli, Romuald Elie, Klaus-Robert Müller +3Score Matching Diffusion Model Sampling
1Google DeepMind · 2BIFOLD – Berlin Institute for the Foundations of Learning and Data · 3Machine Learning Group, Technische Universität Berlin +2
Demystifying MaskGIT Sampler and Beyond: Adaptive Order Selection in Masked Diffusion
Oct 6, 2025Satoshi Hayakawa, Yuhta Takida, Masaaki Imaizumi +2Diffusion Model Sampling Diffusion Sampling
Sony Group Corporation · Sony AI · The University of Tokyo
MACS: Measurement-Aware Consistency Sampling for Inverse Problems
Oct 2, 2025Amirreza Tanevardi, Pooria Abbas Rad Moghadam, Seyed Mohammad Eshtehardian +2Diffusion Model Sampling Inverse Problems
Department of Electrical Engineering Sharif University of Technology Tehran, Iran · Electronics Research Institute Sharif University of Technology Tehran, Iran
Fast Convergence for High-Order ODE Solvers in Diffusion Probabilistic Models
Date pendingDaniel Zhengyu Huang, Jiaoyang Huang, Zhengjiang LinDiffusion Model Sampling Diffusion Sampling
Beijing International Center for Mathematical Research, Center for Machine Learning Research, Peking University, Beijing, China · Department of Statistics and Data Science, University of Pennsylvania, Philadelphia, PA, USA · Department of Mathematics, Massachusetts Institute of Technology, 77 Massachusetts Ave, 02139 Cambridge MA, USA
Anomaly-Preference Image Generation
Date pendingFuyun Wang, Yuanzhi Wang, Xu Guo +6Diffusion Model Alignment Diffusion Model Sampling
Nanjing University of Science and Technology, Nanjing, China · Beijing Normal University, Beijing, China · China Academy of Space Technology, Beijing, China +1

May 23, 2026, cs.CVJ/K move · Enter open · S save

Self-supervised Dynamic Heterogeneous Degradation Modeling for Unified Zero-Shot Image Restoration

XiaoWan Hu, Jing Yang, HeNan Liu, HuaQiu Li+1

Beihang University · Tsinghua University

Diffusion Models for Image Restoration Diffusion Model Sampling All-in-One Image Restoration Image Restoration

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Zero-shot image restoration provides a flexible way to handle diverse degradations without task-specific training. However, existing methods typically rely on stacked layers or pre-trained features to enhance degradation expression, while overlooking physically consistent priors. The insufficient degradation prompts impose the heavy training burden and high sampling costs during zero-shot diffusion. Moreover, the fixed inference trajectory often collapses to suboptimal solutions under complex corruptions. We observe that heterogeneous degradations can be reparameterized into a minimal set of physically coherent parameters for compact representation. Based on this insight, we first propose a unified physical zero-shot image restoration (UP-ZeroIR) framework that explicitly models heterogeneous degradations into a homogeneous all-in-one distribution. The distribution can be optimized directly in the latent space, enabling principled solution exploration and effective prompt adaptation. Besides, we introduce a dynamic quality-refinement strategy that adaptively adjusts the diffusion trajectory for robust globally optimal convergence. Extensive experiments demonstrate that our method achieves state-of-the-art performance across both single and mixed degradations. Our code is available at https://github.com/yangjinglyy/UP-ZeroIR

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