markov chain monte carlo

MCMC Shape Sampling for Image Segmentation With Nonparametric Shape Priors CVPR 2016 Measuring the reliability of MCMC inference with bidirectional Monte Carlo NeurIPS 2016 Mixing Rates for the Alternating Gibbs Sampler over Restricted Boltzmann Machines and Friends ICML 2016 Monte Carlo Markov Chain Algorithms for Sampling Strongly Rayleigh Distributions and Determinantal Point Processes COLT 2016 Parallel Markov Chain Monte Carlo via Spectral Clustering AISTATS 2016 Pliable Rejection Sampling ICML 2016 Pseudo-Marginal Slice Sampling AISTATS 2016 Scalable MCMC for Mixed Membership Stochastic Blockmodels AISTATS 2016 Scan Order in Gibbs Sampling: Models in Which it Matters and Bounds on How Much NeurIPS 2016 Slice Sampling on Hamiltonian Trajectories ICML 2016 Stochastic Gradient Geodesic MCMC Methods NeurIPS 2016 Stochastic Gradient MCMC with Stale Gradients NeurIPS 2016 Stochastic Gradient Richardson-Romberg Markov Chain Monte Carlo NeurIPS 2016 Stochastic Quasi-Newton Langevin Monte Carlo ICML 2016 String and Membrane Gaussian Processes JMLR 2016 Structure Discovery in Bayesian Networks by Sampling Partial Orders JMLR 2016 Structure Learning in Bayesian Networks of a Moderate Size by Efficient Sampling JMLR 2016 Synthesis of MCMC and Belief Propagation NeurIPS 2016 Towards Unifying Hamiltonian Monte Carlo and Slice Sampling NeurIPS 2016 A Complete Recipe for Stochastic Gradient MCMC NeurIPS 2015 A hybrid sampler for Poisson-Kingman mixture models NeurIPS 2015 Automatic Variational Inference in Stan NeurIPS 2015 Covariance-Controlled Adaptive Langevin Thermostat for Large-Scale Bayesian Sampling NeurIPS 2015 Deep Poisson Factor Modeling NeurIPS 2015 Exponential Integration for Hamiltonian Monte Carlo ICML 2015