Bayesian & Probabilistic

Randomized Pruning: Efficiently Calculating Expectations in Large Dynamic Programs NeurIPS 2009 Reading Tea Leaves: How Humans Interpret Topic Models NeurIPS 2009 Replicated Softmax: an Undirected Topic Model NeurIPS 2009 Rethinking LDA: Why Priors Matter NeurIPS 2009 Riffled Independence for Ranked Data NeurIPS 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 Estimation Using General Likelihoods and Non-Factorial Priors NeurIPS 2009 Sparsistent Learning of Varying-coefficient Models with Structural Changes NeurIPS 2009 Spatial Normalized Gamma Processes NeurIPS 2009 Stable and Efficient Gaussian Process Calculations JMLR 2009 Statistical Models of Linear and Nonlinear Contextual Interactions in Early Visual Processing NeurIPS 2009 STDP enables spiking neurons to detect hidden causes of their inputs NeurIPS 2009 Structural inference affects depth perception in the context of potential occlusion NeurIPS 2009 The Infinite Partially Observable Markov Decision Process NeurIPS 2009 The Wisdom of Crowds in the Recollection of Order Information NeurIPS 2009 Time-rescaling methods for the estimation and assessment of non-Poisson neural encoding models NeurIPS 2009 Time-Varying Dynamic Bayesian Networks NeurIPS 2009 Variational Gaussian-process factor analysis for modeling spatio-temporal data 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 A Convex Upper Bound on the Log-Partition Function for Binary Distributions NeurIPS 2008