Bayesian & Probabilistic

Black-Box Alpha Divergence Minimization ICML 2016 Black-Box Policy Search with Probabilistic Programs AISTATS 2016 Completely random measures for modelling block-structured sparse networks NeurIPS 2016 Compressed Gaussian Process for Manifold Regression JMLR 2016 Compressing Bayes Net CPTs with Persistent Leaky Causes PGM 2016 Computing Lower and Upper Bounds on the Probability of Causal Statements PGM 2016 Conditional Bernoulli Mixtures for Multi-label Classification ICML 2016 Conditional Probability Estimation PGM 2016 Consistent Kernel Mean Estimation for Functions of Random Variables NeurIPS 2016 Contrasting Vertical and Horizontal Transmission of Typological Features COLING 2016 Convex Two-Layer Modeling with Latent Structure NeurIPS 2016 Copula Ordinal Regression for Joint Estimation of Facial Action Unit Intensity CVPR 2016 Coresets for Scalable Bayesian Logistic Regression NeurIPS 2016 Data Programming: Creating Large Training Sets, Quickly NeurIPS 2016 Dealbreaker: A Nonlinear Latent Variable Model for Educational Data ICML 2016 Deep Gaussian Conditional Random Field Network: A Model-Based Deep Network for Discriminative Denoising CVPR 2016 D-GloVe: A Feasible Least Squares Model for Estimating Word Embedding Densities COLING 2016 Disease Trajectory Maps NeurIPS 2016 Distributed Flexible Nonlinear Tensor Factorization NeurIPS 2016 Double Thompson Sampling for Dueling Bandits NeurIPS 2016 d-VMP: Distributed Variational Message Passing PGM 2016 Dynamic Generative model for Diachronic Sense Emergence Detection COLING 2016 Dynamic Sum Product Networks for Tractable Inference on Sequence Data PGM 2016 Early Stopping as Nonparametric Variational Inference AISTATS 2016 Edge-exchangeable graphs and sparsity NeurIPS 2016