Bayesian Inference

Mean Field Variational Approximation for Continuous-Time Bayesian Networks JMLR 2010 Multi-Task Learning using Generalized t Process AISTATS 2010 Near-Optimal Bayesian Active Learning with Noisy Observations NeurIPS 2010 Nonparametric Bayesian Matrix Factorization by Power-EP AISTATS 2010 Nonparametric prior for adaptive sparsity AISTATS 2010 Optimal Bayesian Recommendation Sets and Myopically Optimal Choice Query Sets NeurIPS 2010 PAC-Bayesian Model Selection for Reinforcement Learning NeurIPS 2010 Posterior distributions are computable from predictive distributions AISTATS 2010 Practical Approaches to Principal Component Analysis in the Presence of Missing Values JMLR 2010 Preliminary Results in Decentralized Estimation for Single-Beacon Acoustic Underwater Navigation RSS 2010 Probabilistic Belief Revision with Structural Constraints NeurIPS 2010 Probabilistic Inference and Differential Privacy NeurIPS 2010 Probabilistic Multi-Task Feature Selection NeurIPS 2010 Real-time Multiattribute Bayesian Preference Elicitation with Pairwise Comparison Queries AISTATS 2010 Regret Bounds for Gaussian Process Bandit Problems AISTATS 2010 Sequential Monte Carlo Samplers for Dirichlet Process Mixtures AISTATS 2010 Simple Exponential Family PCA AISTATS 2010 Slice sampling covariance hyperparameters of latent Gaussian models NeurIPS 2010 Sparse Spectrum Gaussian Process Regression JMLR 2010 State-Space Inference and Learning with Gaussian Processes AISTATS 2010 Stochastic Complexity and Generalization Error of a Restricted Boltzmann Machine in Bayesian Estimation JMLR 2010 Switching state space model for simultaneously estimating state transitions and nonstationary firing rates NeurIPS 2010 Tempered Markov Chain Monte Carlo for training of Restricted Boltzmann Machines AISTATS 2010 The Maximal Causes of Natural Scenes are Edge Filters NeurIPS 2010 The Neural Costs of Optimal Control NeurIPS 2010