Bayesian & Probabilistic

Estimating Interventional Outcomes over Time with Causal Normalizing Flow UAI 2026 Estimating Ising Models in Total Variation Distance COLT 2026 Estimating Joint Interventional Distributions from Marginal Interventional Data CLeaR 2026 Event Stream Filtering via Probability Flux Estimation CVPR 2026 Evidential Deep Partial Label Learning to Quantify Disambiguation Uncertainty CVPR 2026 Evidential Transformation Network: Turning Pretrained Models into Evidential Models for Post-hoc Uncertainty Estimation CVPR 2026 Exact Uncertainty Propagation via Gaussian Process Neurons UAI 2026 Exploiting Concavity Information in Contextual Bandit Optimization UAI 2026 Extending Mean-Field Variational Inference via Entropic Regularization: Theory and Computation JMLR 2026 Fast Score-Based Sampling via Log-Concave Reductions COLT 2026 Finding the Signal in the Spam: Jointly Learning Rewards and Worker Reliability from Pairwise Comparisons UAI 2026 Finite Neural Networks as Mixtures of Gaussian Processes: From Provable Error Bounds to Prior Selection JMLR 2026 Functional Stochastic Localization COLT 2026 Fusion of Depth and Semantics for Probabilistic Floorplan Localization CVPR 2026 Gaussian-Mixture Latent Flow for Stochastic 3D Human Motion Prediction CVPR 2026 Generative Bayesian Inference with GANs JMLR 2026 GenMatter: Perceiving Physical Objects with Generative Matter Models CVPR 2026 GP-4DGS: Probabilistic 4D Gaussian Splatting from Monocular Video via Variational Gaussian Processes CVPR 2026 GraphSynth: Resolving the Diversity-Reliability Trade-off with Probabilistic Factor Graphs ACL 2026 Gravitation-Driven Semantic Alignment for Text Video Retrieval CVPR 2026 High-Accuracy Log-Concave Sampling with Stochastic Queries COLT 2026 Higher-Order Hit-&-Run Samplers for Linearly Constrained Densities UAI 2026 Hyperbolic Belief Propagation UAI 2026 Implicit Variational Rejection Sampling UAI 2026 Imprecise Probabilities for Privacy–Accuracy Trade-offs in Bayesian Networks UAI 2026