Bayesian & Probabilistic

Stability of Controllers for Gaussian Process Forward Models ICML 2016 Stable Graphical Models JMLR 2016 Statistical Inference for Pairwise Graphical Models Using Score Matching NeurIPS 2016 Statistical Matching of Discrete Data by Bayesian Networks PGM 2016 Stochastic Gradient Richardson-Romberg Markov Chain Monte Carlo NeurIPS 2016 Structured Generative Models of Continuous Features for Word Sense Induction COLING 2016 Structure Discovery in Bayesian Networks by Sampling Partial Orders JMLR 2016 Student Skill Models in Adaptive Testing PGM 2016 Survey Propagation beyond Constraint Satisfaction Problems AISTATS 2016 Synthesis of MCMC and Belief Propagation NeurIPS 2016 The Factorized Self-Controlled Case Series Method: An Approach for Estimating the Effects of Many Drugs on Many Outcomes JMLR 2016 The Knowledge Gradient for Sequential Decision Making with Stochastic Binary Feedbacks ICML 2016 The Nonparametric Kernel Bayes Smoother AISTATS 2016 The Parameterized Complexity of Approximate Inference in Bayesian Networks PGM 2016 The Sum-Product Theorem: A Foundation for Learning Tractable Models ICML 2016 Tractable Operations for Arithmetic Circuits of Probabilistic Models NeurIPS 2016 UAV Sensor Fusion With Latent-Dynamic Conditional Random Fields in Coronal Plane Estimation CVPR 2016 Unbounded Bayesian Optimization via Regularization AISTATS 2016 Understanding Probabilistic Sparse Gaussian Process Approximations NeurIPS 2016 Universal Models of Multivariate Temporal Point Processes AISTATS 2016 Unsupervised Learning of 3D Structure from Images NeurIPS 2016 Unsupervised Stress Information Labeling Using Gaussian Process Latent Variable Model for Statistical Speech Synthesis Interspeech 2016 Using Social Dynamics to Make Individual Predictions: Variational Inference with a Stochastic Kinetic Model NeurIPS 2016 Variational Bayes on Monte Carlo Steroids NeurIPS 2016 Variational Dependent Multi-output Gaussian Process Dynamical Systems JMLR 2016