Bayesian & Probabilistic

New Liftable Classes for First-Order Probabilistic Inference NeurIPS 2016 Non-negative Matrix Factorization for Discrete Data with Hierarchical Side-Information AISTATS 2016 Nonparametric Network Models for Link Prediction JMLR 2016 Non-Stationary Gaussian Process Regression with Hamiltonian Monte Carlo AISTATS 2016 Observational-Interventional Priors for Dose-Response Learning NeurIPS 2016 On Bayesian Network Inference with Simple Propagation PGM 2016 Online Algorithms for Sum-Product Networks with Continuous Variables PGM 2016 Online Bayesian Moment Matching for Topic Modeling with Unknown Number of Topics NeurIPS 2016 Online Learning With Bayesian Classification Trees CVPR 2016 On Pruning with the MDL Score PGM 2016 On Stacking Probabilistic Temporal Models with Bidirectional Information Flow PGM 2016 On the Importance of Efficient Transition Modeling for Speaker Diarization Interspeech 2016 Operator Variational Inference NeurIPS 2016 Optimality of Belief Propagation for Crowdsourced Classification ICML 2016 Optimistic Gittins Indices NeurIPS 2016 PAC learning of Probabilistic Automaton based on the Method of Moments ICML 2016 Pairwise Choice Markov Chains NeurIPS 2016 Parameter Learning for Log-supermodular Distributions NeurIPS 2016 PHOG: Probabilistic Model for Code ICML 2016 Poisson-Gamma dynamical systems NeurIPS 2016 Predicting Disease Progression with a Model for Multivariate Longitudinal Clinical Data MLHC 2016 Probabilistic Approaches to the AXB = YCZ Calibration Problem in Multi-Robot Systems RSS 2016 Probabilistic Approach Using Joint Clean and Noisy i-Vectors Modeling for Speaker Recognition Interspeech 2016 Probabilistic Approximate Least-Squares AISTATS 2016 Probabilistic Graphical Models Specified by Probabilistic Logic Programs: Semantics and Complexity PGM 2016