Markov Chain Monte Carlo

Gaussian process modulated renewal processes NeurIPS 2011 Image Parsing with Stochastic Scene Grammar NeurIPS 2011 Modelling Genetic Variations using Fragmentation-Coagulation Processes NeurIPS 2011 On Tracking The Partition Function NeurIPS 2011 Priors over Recurrent Continuous Time Processes NeurIPS 2011 Quasi-Newton Methods for Markov Chain Monte Carlo NeurIPS 2011 Query-Aware MCMC NeurIPS 2011 Simultaneous Sampling and Multi-Structure Fitting with Adaptive Reversible Jump MCMC NeurIPS 2011 Computing Marginal Distributions over Continuous Markov Networks for Statistical Relational Learning NeurIPS 2010 Construction of Dependent Dirichlet Processes based on Poisson Processes NeurIPS 2010 Copula Processes NeurIPS 2010 Gaussian sampling by local perturbations NeurIPS 2010 Improving the Asymptotic Performance of Markov Chain Monte-Carlo by Inserting Vortices NeurIPS 2010 Learning concept graphs from text with stick-breaking priors NeurIPS 2010 (RF)^2 -- Random Forest Random Field NeurIPS 2010 Slice sampling covariance hyperparameters of latent Gaussian models NeurIPS 2010 Tree-Structured Stick Breaking for Hierarchical Data NeurIPS 2010 Accelerating Bayesian Structural Inference for Non-Decomposable Gaussian Graphical Models NeurIPS 2009 Decoupling Sparsity and Smoothness in the Discrete Hierarchical Dirichlet Process 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 Parallel Inference for Latent Dirichlet Allocation on Graphics Processing Units NeurIPS 2009