Bayesian & Probabilistic

Bayesian Matrix Factorization with Non-Random Missing Data using Informative Gaussian Process Priors and Soft Evidences PGM 2016 Bayesian Modeling in Speech Motor Control: A Principled Structure for the Integration of Various Constraints Interspeech 2016 Bayesian Networks: a Combined Tuning Heuristic PGM 2016 Bayesian Networks for Variable Groups PGM 2016 Bayesian Optimization for Likelihood-Free Inference of Simulator-Based Statistical Models JMLR 2016 Bayesian Optimization for Probabilistic Programs NeurIPS 2016 Bayesian Optimization with Robust Bayesian Neural Networks NeurIPS 2016 Bayesian Poisson Tucker Decomposition for Learning the Structure of International Relations ICML 2016 Bayesian Torrent Classification by File Name and Size Only PGM 2016 BayesPy: Variational Bayesian Inference in Python JMLR 2016 Black-Box Alpha Divergence Minimization ICML 2016 Boolean Matrix Factorization and Noisy Completion via Message Passing ICML 2016 Bottom-Up and Top-Down Reasoning With Hierarchical Rectified Gaussians CVPR 2016 Causal Inference through a Witness Protection Program JMLR 2016 Clinical Tagging with Joint Probabilistic Models MLHC 2016 Collapsed Variational Inference for Sum-Product Networks ICML 2016 Completely random measures for modelling block-structured sparse networks NeurIPS 2016 Composing graphical models with neural networks for structured representations and fast inference NeurIPS 2016 Compressing Bayes Net CPTs with Persistent Leaky Causes PGM 2016 Computationally Efficient Bayesian Learning of Gaussian Process State Space Models AISTATS 2016 Conditional Bernoulli Mixtures for Multi-label Classification ICML 2016 Conditional Probability Estimation PGM 2016 Confusions over Time: An Interpretable Bayesian Model to Characterize Trends in Decision Making NeurIPS 2016 Consistent Kernel Mean Estimation for Functions of Random Variables NeurIPS 2016 Constraints Based Convex Belief Propagation NeurIPS 2016