gibbs sampling

Why MCA? Nonlinear sparse coding with spike-and-slab prior for neurally plausible image encoding NeurIPS 2012 A Spike and Slab Restricted Boltzmann Machine AISTATS 2011 Automated Refinement of Bayes Networks' Parameters based on Test Ordering Constraints NeurIPS 2011 Bayesian Bias Mitigation for Crowdsourcing NeurIPS 2011 Bayesian Partitioning of Large-Scale Distance Data NeurIPS 2011 Collective Graphical Models NeurIPS 2011 Dependent Hierarchical Beta Process for Image Interpolation and Denoising AISTATS 2011 Distance Dependent Chinese Restaurant Processes JMLR 2011 Multicore Gibbs Sampling in Dense, Unstructured Graphs AISTATS 2011 Multiscale Community Blockmodel for Network Exploration AISTATS 2011 Parallel Gibbs Sampling: From Colored Fields to Thin Junction Trees AISTATS 2011 Priors over Recurrent Continuous Time Processes NeurIPS 2011 Query-Aware MCMC NeurIPS 2011 Spectral Chinese Restaurant Processes: Nonparametric Clustering Based on Similarities AISTATS 2011 Approximate Inference by Compilation to Arithmetic Circuits NeurIPS 2010 A Study of Approximate Inference in Probabilistic Relational Models ACML 2010 Construction of Dependent Dirichlet Processes based on Poisson Processes NeurIPS 2010 FastInf: An Efficient Approximate Inference Library JMLR 2010 Gaussian sampling by local perturbations NeurIPS 2010 Joint Analysis of Time-Evolving Binary Matrices and Associated Documents NeurIPS 2010 Parallelizable Sampling of Markov Random Fields AISTATS 2010 Supervised Dimension Reduction Using Bayesian Mixture Modeling AISTATS 2010 Decoupling Sparsity and Smoothness in the Discrete Hierarchical Dirichlet Process NeurIPS 2009 Distributed Algorithms for Topic Models JMLR 2009 Linearly constrained Bayesian matrix factorization for blind source separation NeurIPS 2009