Score-Based Generative Modeling

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6 papers in the last four weeks, with none the four weeks before. 0.1% of all new papers.

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Riemannian Diffusion Models on General Manifolds via Physics-Informed Neural Networks
May 29, 2026Gyeonghoon Ko, Juho LeePhysics-Informed Diffusion Models Physics-Informed Generative Modeling
1Korea Advanced Institute of Science and Technology, Korea.
The Score Hamiltonian: Mapping Diffusion Models to Adiabatic Transport
May 28, 2026Peter Halmos, Boris HaninDiffusion Sampling Score-Based Generative Modeling
Computer Science Department, Princeton University. · ORFE Department, Princeton University.
GenSBI: Generative Methods for Simulation-Based Inference in JAX
May 26, 2026Aurelio AmerioFlow Matching Simulation-Based Inference
Instituto de Física Corpuscular (IFIC) Universitat de València & CSIC València, Spain
Rao-Blackwellized Score Matching on Manifolds
May 25, 2026Divit RawalScore Matching Score-Based Generative Modeling
Department of Statistics, University of California, Berkeley, Berkeley CA, U.S.A..
Diffusion-based Denoising Beats Vanilla Score Matching in Parameter Estimation: A Theoretical Explanation
May 21, 2026Benedikt Lütke Schwienhorst, Nadja Klein, Johannes LedererScore Matching Parameter Estimation
Department of Mathematics University of Hamburg Hamburg, Germany · Scientific Computing Center Karlsruhe Institute of Technology2026 Karlsruhe, Germany · Department of MathematicsMay University of Hamburg Hamburg, Germany21
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
Physics-Informed Generative Solver: Bridging Data-Driven Priors and Conservation Laws for Stable Spatiotemporal Field Reconstruction
May 21, 2026Ziyuan Zhu, Keyu Hu, Zhifei Chen +10Physics-Informed Generative Modeling Physics-Informed ML
School of Advanced Manufacturing Engineering, Nanjing University, Suzhou, 215163, China. · National Laboratory of Solid State Microstructures, Nanjing University, Nanjing, 210093, China. · Suzhou Acoustics Industry Technology Research Institute Co., Ltd., Suzhou, 215513, China. +8
Tweedie's Formulae and Diffusion Generative Models Beyond Gaussian
May 19, 2026Wenpin Tang, Nizar Touzi, Zikun Zhang +1Stochastic Differential Equations Time Series Generation
Reducing Diffusion Model Memorization with Higher Order Langevin Dynamics
May 18, 2026Benjamin Sterling, Mónica F. Bugallo, Tom TirerLangevin Dynamics Memorization in Generative Models
Department of Applied Math & Statistics Stony Brook University Stony Brook, NY 11790 · Department of Electrical and Computer Engineering Stony Brook University Stony Brook, NY 11790 · Faculty of Engineering Bar-Ilan University Ramat-Gan 5290002, Israel
Provably Learning Diffusion Models under the Manifold Hypothesis: Collapse and Refine
May 16, 2026Wei Huang, Andi Han, Mingyuan Bai +4Latent Diffusion Models Manifold Learning
RIKEN AIP & The Institute of Statistical Mathematics · University of Sydney · Agency for Science, Technology and Research & The Institute of Statistical Mathematics +4
Towards Generalized Image Manipulation Localization via Score-based Model
May 16, 2026Yunfei Wang, Bo Du, Zhe Yang +4Image Forgery Detection Image Forgery Localization
Sichuan University · Chengdu, China
Intrinsic Wasserstein Rates for Score-Based Generative Models on Smooth Manifolds
May 15, 2026Guoji Fu, Taiji Suzuki, Wee Sun Lee +1Intrinsic Dimensionality Generative Modeling
National University of Singapore · The University of Tokyo · RIKEN Center for Advanced Intelligence Project +2
Proximal-Based Generative Modeling for Bayesian Inverse Problems
May 13, 2026Boyang Zhang, Zhiguo Wang, Ya-Feng LiuScore Matching Bayesian Inverse Problems
School of Advanced Interdisciplinary Sciences, University of Chinese Academy of Sciences, Beijing, China · Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China · School of Mathematics, Sichuan University, Chengdu, China +2
Free Energy Manifold: Score-Based Inference for Hybrid Bayesian Networks
May 11, 2026Cheol Young Park, Shou MatsumotoBayesian Networks Energy-Based Models
ATOS Co., Ltd., 273, Digital-ro, Guro-gu, Seoul, 08381, Republic of Korea · C5I Center, George Mason University, Fairfax, VA 22030, USA
Learning Unified Representations of Normalcy for Time Series Anomaly Detection
May 10, 2026Prithul Sarker, Sushmita Sarker, Nicholas G. Murray +1Reconstruction-Based Anomaly Detection Unsupervised Anomaly Detection
University of Nevada, Reno
Metropolis-Adjusted Diffusion Models
May 10, 2026Kevin H. Lam, Tyler Farghly, Christopher Williams +3Markov Chain Monte Carlo Diffusion Sampling
Department of Statistics, University of Oxford · Inria, CNRS, École Normale Supérieure, PSL Research University · Department of Mathematical Sciences, University of Copenhagen
Slowly Annealed Langevin Dynamics: Theory and Applications to Training-Free Guided Generation
May 8, 2026Atsushi Nitanda, Dake Bu, Yueming Lyu +1Diffusion Model Guidance Langevin Dynamics
Agency for Science, Technology and Research (A⋆STAR) · Nanyang Technological University · City University of Hong Kong
Generative Modeling with Flux Matching
May 8, 2026Peter Pao-Huang, Xiaojie Qiu, Stefano ErmonGenerative Modeling Score-Based Generative Modeling
Department of Computer Science, Stanford University · Department of Genetics, Stanford University
Kurtosis-Guided Denoising Score Matching for Tabular Anomaly Detection
May 7, 2026Victor Livernoche, Jie Zan, Reihaneh RabbanyTabular Anomaly Detection Unsupervised Anomaly Detection
McGill University, Mila, Montréal, Canada
A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models
May 7, 2026Aditya Ranganath, Mukesh SinghalFlow Matching Generative Modeling
Center for Applied Scientific Computing Lawrence Livermore National Laboratory Livermore, CA 94551, USA · Department of Electrical Engineering University of California Merced, CA 95343, USA
The Interplay of Data Structure and Imbalance in the Learning Dynamics of Diffusion Models
May 7, 2026Flavio Nicoletti, Chenxiao Ma, Enrico Ventura +2Class-Imbalanced Learning Score-Based Generative Modeling
Data Science and AI, Computer Science and Engineering Department, Chalmers University of Technology and University of Gothenburg · International School of Advanced Studies (SISSA), Trieste, Italy · Department of Computing Sciences, Bocconi University, Milano, Italy +2
Predictive-Generative Drift Decomposition for Speech Enhancement and Separation
May 7, 2026Julius Richter, Yoshiki Masuyama, Christoph Boeddeker +3Stochastic Interpolants Speech Processing
MERL Cambridge, MA, USA
Stochastic Schrödinger Diffusion Models for Pure-State Ensemble Generation
May 5, 2026Jian Xu, Wei Chen, Shigui Li +5Quantum Generative Modeling Quantum State Preparation
1RIKEN iTHEMS · 2RIKEN AIP · 3South China University of Technology +2
A unified perspective on fine-tuning and sampling with diffusion and flow models
Apr 30, 2026Carles Domingo-Enrich, Yuanqi Du, Michael S. AlbergoStochastic Optimal Control Diffusion Sampling
Microsoft Research New England · Harvard University, Kempner Institute
Quantum Dynamics via Score Matching on Bohmian Trajectories
Apr 28, 2026Lei WangScore Matching PDE Solving
Beijing National Laboratory for Condensed Matter Physics and Institute of Physics, Chinese Academy of Sciences, Beijing 100190, China
Symmetric Equilibrium Propagation for Thermodynamic Diffusion Training
Apr 26, 2026Aditi DeEquilibrium Propagation Thermodynamic Computing
Score-Based Matching with Target Guidance for Cryo-EM Denoising
Apr 20, 2026Xiaoqi Wu, Xueying Zhan, Wen Li +3Cryo-Electron Microscopy Score-Based Generative Modeling
Carnegie Mellon University · Towson University
Reward Score Matching: Unifying Reward-based Fine-tuning for Flow and Diffusion Models
Apr 19, 2026Jeongjae Lee, Jinho Chang, Jeongsol Kim +1Diffusion Model Alignment Diffusion Model Fine-Tuning
Graduate School of AI KAIST, Korea
An Analysis of Regularization and Fokker-Planck Residuals in Diffusion Models for Image Generation
Apr 16, 2026Onno Niemann, Gonzalo Martínez Muñoz, Alberto Suárez GonzalezDiffusion-Based Image Generation Score-Based Generative Modeling
Universidad Autónoma de Madrid
Asymptotic Learning Curves for Diffusion Models with Random Features Score and Manifold Data
Mar 24, 2026Anand Jerry George, Nicolas MacrisIntrinsic Dimensionality Score-Based Generative Modeling
École Polytechnique Fédérale de Lausanne (EPFL), Lab for Statistical Mechanics of Inference in Large Systems (SMILS), CH-1015 Lausanne, Switzerland

May 29, 2026, cs.LGJ/K move · Enter open · S save

Riemannian Diffusion Models on General Manifolds via Physics-Informed Neural Networks

Gyeonghoon Ko, Juho Lee

1Korea Advanced Institute of Science and Technology, Korea.

Physics-Informed Diffusion Models Physics-Informed Generative Modeling Diffusion Model Sampling Score-Based Generative Modeling Diffusion Models

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Riemannian diffusion models generalize score-based generative modeling to manifold-supported data via stochastic diffusion equations on the manifold. However, training requires sampling from and differentiating the manifold heat kernel, which is rarely available in closed form beyond a few highly symmetric manifolds. We propose a general approach that approximates the heat kernel by directly solving the manifold heat equation with a physics-informed neural network (PINN). Given an explicit manifold specification, we choose a coordinate system, derive the corresponding heat (Fokker--Planck) equation and a short-time asymptotic approximation, and then train a PINN to learn the log heat kernel. The resulting surrogate enables both forward noising (heat-kernel sampling) and conditional-score evaluation for denoising score matching. We demonstrate the method on diverse manifolds including

S^2

SO(3)

\mathrm{SPD}(n)

, and permutation-quotiented point clouds.

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Latest papers 71