Bayesian & Probabilistic

Rethinking LDA: Why Priors Matter NeurIPS 2009 Riffled Independence for Ranked Data NeurIPS 2009 Robustness of the Unscented Kalman filter for state and parameter estimation in an elastic transmission RSS 2009 Sensitivity analysis in HMMs with application to likelihood maximization NeurIPS 2009 Sequential effects reflect parallel learning of multiple environmental regularities NeurIPS 2009 Sharing Features among Dynamical Systems with Beta Processes NeurIPS 2009 Sparse and Locally Constant Gaussian Graphical Models 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 Structural inference affects depth perception in the context of potential occlusion NeurIPS 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 'tree-dependent components' of natural scenes are edge filters NeurIPS 2009 The Wisdom of Crowds in the Recollection of Order Information NeurIPS 2009 Time-Varying Dynamic Bayesian Networks NeurIPS 2009 Toward Provably Correct Feature Selection in Arbitrary Domains NeurIPS 2009 Training Factor Graphs with Reinforcement Learning for Efficient MAP Inference NeurIPS 2009 Variational Inference for the Nested Chinese Restaurant Process NeurIPS 2009 Which graphical models are difficult to learn? NeurIPS 2009 Whose Vote Should Count More: Optimal Integration of Labels from Labelers of Unknown Expertise 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 Adapting to a Market Shock: Optimal Sequential Market-Making NeurIPS 2008