markov chain monte carlo

Scalable Adaptation of State Complexity for Nonparametric Hidden Markov Models NeurIPS 2015 Scalable Nonparametric Bayesian Inference on Point Processes with Gaussian Processes ICML 2015 Subgraph Matching Using Compactness Prior for Robust Feature Correspondence CVPR 2015 The Fundamental Incompatibility of Scalable Hamiltonian Monte Carlo and Naive Data Subsampling ICML 2015 Transformation of Markov Random Fields for Marginal Distribution Estimation CVPR 2015 Tree-Guided MCMC Inference for Normalized Random Measure Mixture Models NeurIPS 2015 Variational Consensus Monte Carlo NeurIPS 2015 A Compilation Target for Probabilistic Programming Languages ICML 2014 A Level-set Hit-and-run Sampler for Quasi-Concave Distributions AISTATS 2014 A Mixture of Manhattan Frames: Beyond the Manhattan World CVPR 2014 A New Approach to Probabilistic Programming Inference AISTATS 2014 Austerity in MCMC Land: Cutting the Metropolis-Hastings Budget ICML 2014 Automated Variational Inference for Gaussian Process Models NeurIPS 2014 Bayesian Nonlinear Support Vector Machines and Discriminative Factor Modeling NeurIPS 2014 Bayesian Sampling Using Stochastic Gradient Thermostats NeurIPS 2014 Beta Diffusion Trees ICML 2014 Deep Joint Task Learning for Generic Object Extraction NeurIPS 2014 Distributed Bayesian Posterior Sampling via Moment Sharing NeurIPS 2014 Distributed Stochastic Gradient MCMC ICML 2014 Efficient Continuous-Time Markov Chain Estimation ICML 2014 Efficient Nonlinear Markov Models for Human Motion CVPR 2014 Fast Sampling-Based Inference in Balanced Neuronal Networks NeurIPS 2014 Gaussian Approximation of Collective Graphical Models ICML 2014 Generating Efficient MCMC Kernels from Probabilistic Programs AISTATS 2014 Hamiltonian Monte Carlo Without Detailed Balance ICML 2014