markov chain monte carlo

Matrix-Variate Dirichlet Process Mixture Models AISTATS 2010 Parallelizable Sampling of Markov Random Fields AISTATS 2010 Slice sampling covariance hyperparameters of latent Gaussian models NeurIPS 2010 Tempered Markov Chain Monte Carlo for training of Restricted Boltzmann Machines AISTATS 2010 Tree-Structured Stick Breaking for Hierarchical Data NeurIPS 2010 Variational Inference over Combinatorial Spaces NeurIPS 2010 Accelerating Bayesian Structural Inference for Non-Decomposable Gaussian Graphical Models NeurIPS 2009 Bayesian Belief Polarization NeurIPS 2009 Gaussian process regression with Student-t likelihood NeurIPS 2009 Large Scale Nonparametric Bayesian Inference: Data Parallelisation in the Indian Buffet Process NeurIPS 2009 Learning in Markov Random Fields using Tempered Transitions NeurIPS 2009 Learning models of object structure NeurIPS 2009 Linearly constrained Bayesian matrix factorization for blind source separation NeurIPS 2009 Non-stationary continuous dynamic Bayesian networks NeurIPS 2009 Perceptual Multistability as Markov Chain Monte Carlo Inference NeurIPS 2009 Randomized Pruning: Efficiently Calculating Expectations in Large Dynamic Programs NeurIPS 2009 Sharing Features among Dynamical Systems with Beta Processes NeurIPS 2009 Spatial Normalized Gamma Processes NeurIPS 2009 The Wisdom of Crowds in the Recollection of Order Information NeurIPS 2009 A ``Shape Aware'' Model for semi-supervised Learning of Objects and its Context NeurIPS 2008 Efficient Inference in Phylogenetic InDel Trees NeurIPS 2008 Efficient Sampling for Gaussian Process Inference using Control Variables NeurIPS 2008 Evaluating probabilities under high-dimensional latent variable models NeurIPS 2008 Multiscale Random Fields with Application to Contour Grouping NeurIPS 2008 Nonparametric Bayesian Learning of Switching Linear Dynamical Systems NeurIPS 2008