Variational Inference

A Stick-Breaking Likelihood for Categorical Data Analysis with Latent Gaussian Models AISTATS 2012 Bayesian Probabilistic Co-Subspace Addition NeurIPS 2012 Bayesian Warped Gaussian Processes NeurIPS 2012 Fast Bayesian Inference for Non-Conjugate Gaussian Process Regression NeurIPS 2012 Homeostatic plasticity in Bayesian spiking networks as Expectation Maximization with posterior constraints NeurIPS 2012 Meta-Gaussian Information Bottleneck NeurIPS 2012 Perfect Dimensionality Recovery by Variational Bayesian PCA NeurIPS 2012 Phoneme Classification using Constrained Variational Gaussian Process Dynamical System NeurIPS 2012 Small-Variance Asymptotics for Exponential Family Dirichlet Process Mixture Models NeurIPS 2012 The variational hierarchical EM algorithm for clustering hidden Markov models NeurIPS 2012 Truly Nonparametric Online Variational Inference for Hierarchical Dirichlet Processes NeurIPS 2012 Truncation-free Online Variational Inference for Bayesian Nonparametric Models NeurIPS 2012 Variational Inference for Crowdsourcing NeurIPS 2012 Approximate Marginals in Latent Gaussian Models JMLR 2011 Generalized Beta Mixtures of Gaussians NeurIPS 2011 Global Solution of Fully-Observed Variational Bayesian Matrix Factorization is Column-Wise Independent NeurIPS 2011 Non-conjugate Variational Message Passing for Multinomial and Binary Regression NeurIPS 2011 Online Variational Inference for the Hierarchical Dirichlet Process AISTATS 2011 Practical Variational Inference for Neural Networks NeurIPS 2011 Probabilistic Joint Image Segmentation and Labeling NeurIPS 2011 Select and Sample - A Model of Efficient Neural Inference and Learning NeurIPS 2011 t-divergence Based Approximate Inference NeurIPS 2011 Variational Gaussian Process Dynamical Systems NeurIPS 2011 Variational Learning for Recurrent Spiking Networks NeurIPS 2011 Approximate Inference by Compilation to Arithmetic Circuits NeurIPS 2010