Bayesian Learning

On the Convergence of Stochastic Gradient MCMC Algorithms with High-Order Integrators NeurIPS 2015 On-the-Job Learning with Bayesian Decision Theory NeurIPS 2015 Particle Gibbs for Infinite Hidden Markov Models NeurIPS 2015 Privacy for Free: Posterior Sampling and Stochastic Gradient Monte Carlo ICML 2015 Probabilistic Backpropagation for Scalable Learning of Bayesian Neural Networks ICML 2015 Reactive bandits with attitude AISTATS 2015 Scalable Adaptation of State Complexity for Nonparametric Hidden Markov Models NeurIPS 2015 Segregated Graphs and Marginals of Chain Graph Models NeurIPS 2015 The Bayesian Echo Chamber: Modeling Social Influence via Linguistic Accommodation AISTATS 2015 The Poisson Gamma Belief Network NeurIPS 2015 Tractable Bayesian Network Structure Learning with Bounded Vertex Cover Number NeurIPS 2015 Weight Uncertainty in Neural Network ICML 2015 A Bayesian Framework for Online Classifier Ensemble ICML 2014 A Bayesian model for identifying hierarchically organised states in neural population activity NeurIPS 2014 A Bayesian Wilcoxon signed-rank test based on the Dirichlet process ICML 2014 Adaptive Variable Clustering in Gaussian Graphical Models AISTATS 2014 Advances in Learning Bayesian Networks of Bounded Treewidth NeurIPS 2014 A Framework for Testing Identifiability of Bayesian Models of Perception NeurIPS 2014 Analysis of Brain States from Multi-Region LFP Time-Series NeurIPS 2014 Analysis of Variational Bayesian Latent Dirichlet Allocation: Weaker Sparsity Than MAP NeurIPS 2014 A reversible infinite HMM using normalised random measures ICML 2014 A Statistical Decision-Theoretic Framework for Social Choice NeurIPS 2014 Augur: Data-Parallel Probabilistic Modeling NeurIPS 2014 Automated Variational Inference for Gaussian Process Models NeurIPS 2014 Bayes-Adaptive Simulation-based Search with Value Function Approximation NeurIPS 2014