Bayesian Inference

Semi-Separable Hamiltonian Monte Carlo for Inference in Bayesian Hierarchical Models NeurIPS 2014 Sequential Monte Carlo for Graphical Models NeurIPS 2014 Sparse Bayesian structure learning with “dependent relevance determination” priors NeurIPS 2014 Spectral Methods for Indian Buffet Process Inference NeurIPS 2014 Stochastic variational inference for hidden Markov models NeurIPS 2014 The Bayesian Case Model: A Generative Approach for Case-Based Reasoning and Prototype Classification NeurIPS 2014 Thompson Sampling for Complex Online Problems ICML 2014 Tracking on the Product Manifold of Shape and Orientation for Tractography from Diffusion MRI CVPR 2014 Tree-structured Gaussian Process Approximations NeurIPS 2014 Variational Gaussian Inference for Bilinear Models of Count Data ACML 2014 Active Bayesian Perception for Simultaneous Object Localization and Identification RSS 2013 Active Learning for Probabilistic Hypotheses Using the Maximum Gibbs Error Criterion NeurIPS 2013 A Determinantal Point Process Latent Variable Model for Inhibition in Neural Spiking Data NeurIPS 2013 A Joint Model for 2D and 3D Pose Estimation from a Single Image CVPR 2013 Analyzing Hogwild Parallel Gaussian Gibbs Sampling NeurIPS 2013 A Non-parametric Bayesian Network Prior of Human Pose ICCV 2013 Approximate Bayesian Image Interpretation using Generative Probabilistic Graphics Programs NeurIPS 2013 A simple example of Dirichlet process mixture inconsistency for the number of components NeurIPS 2013 Auxiliary-variable Exact Hamiltonian Monte Carlo Samplers for Binary Distributions NeurIPS 2013 Bayesian Depth-from-Defocus with Shading Constraints CVPR 2013 Bayesian entropy estimation for binary spike train data using parametric prior knowledge NeurIPS 2013 Bayesian Hierarchical Community Discovery NeurIPS 2013 Bayesian Inference and Learning in Gaussian Process State-Space Models with Particle MCMC NeurIPS 2013 Bayesian Inference and Online Experimental Design for Mapping Neural Microcircuits NeurIPS 2013 Bayesian inference as iterated random functions with applications to sequential inference in graphical models NeurIPS 2013