Bayesian & Probabilistic

Information-Theoretic Bayesian Optimization for Bilevel Optimization Problems UAI 2026 Information Theoretic Bayesian Optimization over the Probability Simplex UAI 2026 Instrumental and Proximal Causal Inference with Gaussian Processes UAI 2026 Inter-Photon-Limited Videography CVPR 2026 KMM-CP: Practical Conformal Prediction under Covariate Shift via Selective Kernel Mean Matching UAI 2026 Kronecker-Structured Nonparametric Spatiotemporal Point Processes UAI 2026 LazyDINO: Fast, Scalable, and Efficiently Amortized Bayesian Inversion via Structure-Exploiting and Surrogate-Driven Measure Transport JMLR 2026 Learning Bayesian and Markov Networks with an Unreliable Oracle UAI 2026 Learning Bayesian Network Classifiers to Minimize Class Variable Parameters JMLR 2026 Learning Dynamics from Input-Output Data with Hamiltonian Gaussian Processes L4DC 2026 Learning Latent Energy-Based Models via Interacting Particle Langevin Dynamics UAI 2026 LLM-Guided Probabilistic Fusion for Label-Efficient Document Layout Analysis CVPR 2026 Making the Classification Explanation Faithful to the Confidence Score CVPR 2026 Markovian Scale Prediction: A New Era of Visual Autoregressive Generation CVPR 2026 Maximally Robust Satisficing Bayesian Optimization UAI 2026 Mixing times of data-augmentation Gibbs samplers for high-dimensional probit regression JMLR 2026 Model Merging as Probabilistic Inference in Fine-Tuning Parameter Space UAI 2026 More is more: leveraging multi-rater information for whole slide images grading via virtual expert panel MIDL 2026 Multi-modal Test-time Adaptation via Adaptive Probabilistic Gaussian Calibration CVPR 2026 Multiwinner Voting with Interval Preferences under Incomplete Information UAI 2026 Nearly Minimax Discrete Distribution Estimation in Kullback-Leibler Divergence with High Probability ALT 2026 Neural Diffusion Intensity Models for Point Process Data UAI 2026 Neural Mixture Density Processes CVPR 2026 Online Bernstein-von Mises theorem JMLR 2026 Optimal Conformal Prediction under Epistemic Uncertainty UAI 2026