Bayesian Learning

Nonparametric Bayesian Texture Learning and Synthesis NeurIPS 2009 Nonparametric Latent Feature Models for Link Prediction NeurIPS 2009 Non-stationary continuous dynamic Bayesian networks NeurIPS 2009 Particle-based Variational Inference for Continuous Systems NeurIPS 2009 Posterior vs Parameter Sparsity in Latent Variable Models NeurIPS 2009 Python Environment for Bayesian Learning: Inferring the Structure of Bayesian Networks from Knowledge and Data JMLR 2009 Rethinking LDA: Why Priors Matter NeurIPS 2009 Robustness of the Unscented Kalman filter for state and parameter estimation in an elastic transmission RSS 2009 Sequential effects reflect parallel learning of multiple environmental regularities NeurIPS 2009 Sharing Features among Dynamical Systems with Beta Processes NeurIPS 2009 Sparse Estimation Using General Likelihoods and Non-Factorial Priors NeurIPS 2009 Spatial Normalized Gamma Processes NeurIPS 2009 Speeding up Magnetic Resonance Image Acquisition by Bayesian Multi-Slice Adaptive Compressed Sensing NeurIPS 2009 Strong Limit Theorems for the Bayesian Scoring Criterion in Bayesian Networks JMLR 2009 The Hidden Life of Latent Variables: Bayesian Learning with Mixed Graph Models JMLR 2009 The Infinite Partially Observable Markov Decision Process NeurIPS 2009 The Wisdom of Crowds in the Recollection of Order Information NeurIPS 2009 Time-Varying Dynamic Bayesian Networks NeurIPS 2009 Variational Inference for the Nested Chinese Restaurant Process NeurIPS 2009 Accelerating Bayesian Inference over Nonlinear Differential Equations with Gaussian Processes NeurIPS 2008 Active Learning of Causal Networks with Intervention Experiments and Optimal Designs JMLR 2008 Adaptive Body Scheme Models for Robust Robotic Manipulation RSS 2008 Analyzing human feature learning as nonparametric Bayesian inference NeurIPS 2008 An Efficient Sequential Monte Carlo Algorithm for Coalescent Clustering NeurIPS 2008 Asynchronous Distributed Learning of Topic Models NeurIPS 2008