Bayesian & Probabilistic

Accelerating Constrained Sampling: A Large Deviations Approach JMLR 2026 Active Constraint Learning in High Dimensions from Demonstrations L4DC 2026 Adaptive Nonparametric Perturbations of Parametric Models with Generalized Bayes JMLR 2026 A Distribution Testing Approach to Clustering Distributions COLT 2026 Almost Linear Convergence under Minimal Score Assumptions: Quantized Transition Diffusion COLT 2026 Anomaly detection in time-series via inductive biases in the latent space of conditional normalizing flows UAI 2026 A Polynomial Chaos Framework for Causal Discovery in Nonlinear Uncertain Systems CVPR 2026 Balancing Expressivity and Learnability in Quantum Kernel Bandit Optimization UAI 2026 Bayesian Causal Discovery in Directed Cyclic Graphs with Closed-Form Lag Bayes Factors UAI 2026 Beyond Mean-Field: Tree-Copula Variational Autoencoders for Structured Latent Dependencies UAI 2026 Bidirectional Normalizing Flow: From Data to Noise and Back CVPR 2026 Bregman contrastive estimation as a general framework for learning unnormalized models: Efficiency, robustness and optimal noise UAI 2026 BUSSARD: Normalizing Flows for Bijective Universal Scene-Specific Anomalous Relationship Detection CVPR 2026 Causal Discovery in Mixtures of Populations UAI 2026 Coarsening Causal DAG Models CLeaR 2026 COBALT: Censored Optimization and Bayesian Active Learning Techniques 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 Credal Concept Bottleneck Models for Epistemic–Aleatoric Uncertainty Decomposition ACL 2026 DABO: Difficulty-Aware Bayesian Optimization with Diffusion-Learned Priors CVPR 2026 DS-Compatible Log-Linear Reliability with KL-Prox EM: Monotone Ascent, Identifiability, and Generalization ALT 2026 Efficient KL Divergence Estimation via Truncated Top-K Integration for Large Language Models ACL 2026 Efficient Sampling with Discrete Diffusion Models: Sharp and Adaptive Guarantees COLT 2026 Efficient State and Parameter Estimation of Nonlinear State-Space Models through Probabilistic Optimal Control L4DC 2026