markov chain monte carlo

Hamming Ball Auxiliary Sampling for Factorial Hidden Markov Models NeurIPS 2014 Incremental Tree-Based Inference with Dependent Normalized Random Measures AISTATS 2014 Kernel Adaptive Metropolis-Hastings ICML 2014 Learning Modular Structures from Network Data and Node Variables ICML 2014 Lower Bounds for the Gibbs Sampler over Mixtures of Gaussians ICML 2014 Multiscale Fields of Patterns NeurIPS 2014 Parallel MCMC with Generalized Elliptical Slice Sampling JMLR 2014 Parallel Sampling of HDPs using Sub-Cluster Splits NeurIPS 2014 Persistent Monitoring of Stochastic Spatio-temporal Phenomena with a Small Team of Robots RSS 2014 PEWA: Patch-based Exponentially Weighted Aggregation for image denoising NeurIPS 2014 Pitfalls in the use of Parallel Inference for the Dirichlet Process ICML 2014 Poisson Process Jumping between an Unknown Number of Rates: Application to Neural Spike Data NeurIPS 2014 Positive Curvature and Hamiltonian Monte Carlo NeurIPS 2014 Projecting Markov Random Field Parameters for Fast Mixing NeurIPS 2014 Sampling for Inference in Probabilistic Models with Fast Bayesian Quadrature NeurIPS 2014 Scanline Sampler without Detailed Balance: An Efficient MCMC for MRF Optimization CVPR 2014 Semi-Separable Hamiltonian Monte Carlo for Inference in Bayesian Hierarchical Models NeurIPS 2014 Sequential Monte Carlo for Graphical Models NeurIPS 2014 SMERED: A Bayesian Approach to Graphical Record Linkage and De-duplication AISTATS 2014 Sparse Bayesian Variable Selection for the Identification of Antigenic Variability in the Foot-and-Mouth Disease Virus AISTATS 2014 Spherical Hamiltonian Monte Carlo for Constrained Target Distributions ICML 2014 Stochastic Gradient Hamiltonian Monte Carlo ICML 2014 The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo JMLR 2014 Towards scaling up Markov chain Monte Carlo: an adaptive subsampling approach ICML 2014 Adaptive Hamiltonian and Riemann Manifold Monte Carlo ICML 2013