posterior inference

K2-ABC: Approximate Bayesian Computation with Kernel Embeddings AISTATS 2016 Markov-modulated Marked Poisson Processes for Check-in Data ICML 2016 Variance Reduction in Stochastic Gradient Langevin Dynamics NeurIPS 2016 Variational Tempering AISTATS 2016 DP-space: Bayesian Nonparametric Subspace Clustering with Small-variance Asymptotics ICML 2015 Expectation Propagation for Rectified Linear Poisson Regression ACML 2015 Infinite Factorial Dynamical Model NeurIPS 2015 Latent Trees for Estimating Intensity of Facial Action Units CVPR 2015 Learning Wake-Sleep Recurrent Attention Models NeurIPS 2015 Measuring Sample Quality with Stein's Method NeurIPS 2015 Metadata Dependent Mondrian Processes ICML 2015 Particle Gibbs for Bayesian Additive Regression Trees AISTATS 2015 Tree-Guided MCMC Inference for Normalized Random Measure Mixture Models NeurIPS 2015 Approximate Slice Sampling for Bayesian Posterior Inference AISTATS 2014 Efficient Gradient-Based Inference through Transformations between Bayes Nets and Neural Nets ICML 2014 Latent Gaussian Models for Topic Modeling AISTATS 2014 Learning Generative Models with Visual Attention NeurIPS 2014 Modeling Correlated Arrival Events with Latent Semi-Markov Processes ICML 2014 Poisson Process Jumping between an Unknown Number of Rates: Application to Neural Spike Data NeurIPS 2014 Preserving Modes and Messages via Diverse Particle Selection ICML 2014 Rectangular Tiling Process ICML 2014 Auxiliary-variable Exact Hamiltonian Monte Carlo Samplers for Binary Distributions NeurIPS 2013 Bayesian Canonical Correlation Analysis JMLR 2013 Bayesian Inference and Online Experimental Design for Mapping Neural Microcircuits NeurIPS 2013 Generalized Random Utility Models with Multiple Types NeurIPS 2013