Score Matching

Follow this topic Ask about this topic

Momentum

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

Jul 13Week of Sep 28

Latest papers 20

All topics

Discrete Score Matching Enables Causal Discovery from Count Data
Sep 30, 2026Euijong Song, Hyewon Park, Gunwoong ParkScore Matching Causal Discovery
Department of Statistics Seoul National University, Korea · Interdisciplinary Program in Artificial Intelligence; Institute for Data Innovation in Science, Seoul National University, Korea
Safe Score Matching: Diffusion Policies with Hamilton-Jacobi Reachability for Online Safe Reinforcement Learning
Sep 27, 2026Boyang Li, Matthew Kim, Sylvia Lee HerbertScore Matching Constrained RL
University of California San Diego
Generalised Score Matching on Convex Domains
Sep 10, 2026Nishanth Shetty, Saisuchith Mahajan, Chandra Sekhar SeelamantulaScore Matching Parameter Estimation
Department of Electrical Engineering Indian Institute of Science, Bengaluru 560012
A Dual Evaluation for Music Transcription
Aug 5, 2026Ping Wang, Guang Yang, Nazif Can Tamer +2Score Matching Automatic Music Transcription
Should the Boundary Term Be Learned in Reflected Diffusion? Conormal Trace and Reflection Masking
Aug 4, 2026Ziyue Wang, Takafumi KanamoriScore Matching Diffusion Models
Institute of Science Tokyo
A Hyperfinite Framework for Score-Based Generative Modeling
Aug 3, 2026Sunder Ram KrishnanScore Matching Stochastic Differential Equations
Kerala School of Mathematics, Kozhikode 673571, Kerala, India.
Score Accuracy Along the Forward Diffusion Does Not Certify Numerical Stability in Diffusion Sampling
Jul 9, 2026Yiwei ZhouScore Matching Diffusion Sampling
Tightening the Score Matching Gap for Diffusion Models
Jul 5, 2026Benjamin Dupuis, Tyler Farghly, Maxime Haddouche +2Score Matching Score-Based Generative Modeling
INRIA - CNRS - D´epartement d’Informatique de l’Ecole Normale Sup´erieure - PSL Research University, France · Ecole Polytechnique - CMAP, IP Paris, Palaiseau, France
Global Convergence of Gradient Descent for Score Matching in Gaussian Mixtures via Reverse Fisher Divergence
Jun 18, 2026Alexander TyurinScore Matching Optimization Convergence Analysis
AXXX, Moscow, Russia · Applied AI Institute, Moscow, Russia
Diffusion Models Observe Only Gradients: A Geometric Perspective on Score Matching Errors
Jun 4, 2026Naïl B. Khelifa, Richard E. Turner, Ramji VenkataramananScore Matching Hodge Decomposition
University of Cambridge
Torus Graphs for Large Scale Neural Phase Analysis
May 30, 2026Jack Goffinet, Casey Hanks, David E. CarlsonScore Matching Sequence Modeling
Department of Computer Science, Duke University, Durham NC, USA · Departments of Civil and Environmental Engineering; Biostatistics and Bioinformatics; and Electrical and Computer Engineering, Duke University, Durham NC, USA
Score-Control for Hallucination Reduction in Diffusion Models
May 29, 2026Mahesh Bhosale, Naresh Kumar Devulapally, Abdul Wasi +3Score Matching Diffusion-Based Image Generation
University at Buffalo Buffalo, NY, USA
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
Finite Sample Bounds for Learning with Score Matching
May 13, 2026Devin Smedira, Abhijith Jayakumar, Sidhant Misra +2Score Matching Sample Complexity
Operations Research Center, Massachusetts Institute of Technology · Theoretical division, Los Alamos National Lab
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
Diffusion model for SU(N) gauge theories
May 7, 2026Javad Komijani, Marina K. Marinkovic, Lara TurgutScore Matching Diffusion Sampling
Institute for Theoretical Physics, ETH Zurich, 8093 Zurich, Switzerland
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
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
Advantage Weighted Matching: Aligning RL with Pretraining in Diffusion Models
Sep 29, 2025Shuchen Xue, Chongjian Ge, Shilong Zhang +2Score Matching Diffusion Model Alignment
UCAS · Adobe Research · HKU +1

Sep 30, 2026, stat.MLJ/K move · Enter open · S save

Discrete Score Matching Enables Causal Discovery from Count Data

Euijong Song, Hyewon Park, Gunwoong Park

Department of Statistics Seoul National University, Korea · Interdisciplinary Program in Artificial Intelligence; Institute for Data Innovation in Science, Seoul National University, Korea

Score Matching Causal Discovery Causal Identifiability Generalized Linear Models

Open paper AskPDF arXiv

Count data pose a challenge for score-matching-based causal discovery: derivatives are unavailable, and simply replacing them with finite differences does not generally suffice for causal discovery. We generalize SCORE's constant-curvature criterion (Rolland et al., 2022) by conditioning on the node's value, yielding the conditional curvature score (CCS) for ordering. We also extend curvature-based parent recovery through the off-diagonal curvature score (OCS), enabling directed acyclic graph (DAG) recovery with both scores constructed from score functions for continuous data and concrete scores for counts. In the bivariate setting, zero CCS exactly characterizes a semiparametric generalized linear model (GLM) conditional form in which the conditional family need not be specified in advance, unlike in classical GLMs. For bivariate semiparametric GLM DAGs under our regularity condition, canonical-parameter nonlinearity is necessary and sufficient for identifiability. In multivariate DAGs, this nonlinearity enables DAG recovery through CCS and OCS. Our framework identifies a new class of semiparametric GLM DAGs that strictly contains the nonlinear Gaussian ANM class identified by SCORE. We introduce DISCO (DIscrete SCOre), a count-DAG recovery algorithm that estimates CCS and OCS using discrete diffusion. Experiments demonstrate accurate DAG recovery across Poisson, negative binomial, binomial, and mixed-family settings, as well as scalability to 1,000-node DAGs on a single GPU.

Momentum

Related topics

Latest papers 20