Markov Chain Monte Carlo

Accelerating Constrained Sampling: A Large Deviations Approach JMLR 2026 Almost Linear Convergence under Minimal Score Assumptions: Quantized Transition Diffusion COLT 2026 Bayesian Causal Discovery in Directed Cyclic Graphs with Closed-Form Lag Bayes Factors UAI 2026 Convergence of Noise-Free Sampling Algorithms with Regularized Wasserstein Proximals JMLR 2026 Counting and Sampling Subsets Using Block Covers UAI 2026 Covariate-dependent Hierarchical Dirichlet Processes JMLR 2026 Efficient Sampling with Discrete Diffusion Models: Sharp and Adaptive Guarantees COLT 2026 Fast Score-Based Sampling via Log-Concave Reductions COLT 2026 Functional Stochastic Localization COLT 2026 GenMatter: Perceiving Physical Objects with Generative Matter Models CVPR 2026 High-Accuracy Log-Concave Sampling with Stochastic Queries COLT 2026 Higher-Order Hit-&-Run Samplers for Linearly Constrained Densities UAI 2026 Learning Latent Energy-Based Models via Interacting Particle Langevin Dynamics UAI 2026 Making the Classification Explanation Faithful to the Confidence Score CVPR 2026 Mixing times of data-augmentation Gibbs samplers for high-dimensional probit regression JMLR 2026 Overlap Analysis of the Shortest Path Problem: Local Search, Landscapes, and Franz-Parisi Potential COLT 2026 Particle GFlowNets: Rethinking Generative Marginalization Models UAI 2026 Polynomial-time sampling despite disorder chaos COLT 2026 ReBaPL: Repulsive Bayesian Prompt Learning CVPR 2026 Scaling Up Bayesian DAG Sampling UAI 2026 Text2Tabular – Reconstructing Tabular Research Data from Scientific Publications ACL 2026 The Geometry of Efficient Nonconvex Sampling COLT 2026 The surrogate Gibbs-posterior of a corrected stochastic MALA: Towards uncertainty quantification for neural networks JMLR 2026 The Within-Orbit Adaptive Leapfrog No-U-Turn Sampler JMLR 2026 Underdamped Langevin MCMC with third order convergence JMLR 2026