variational inference

Supervised Topic Models NeurIPS 2007 The Generalized FITC Approximation NeurIPS 2007 Variational Inference for Diffusion Processes NeurIPS 2007 Variational inference for Markov jump processes NeurIPS 2007 Accelerated Variational Dirichlet Process Mixtures NeurIPS 2006 A Collapsed Variational Bayesian Inference Algorithm for Latent Dirichlet Allocation NeurIPS 2006 Approximate inference using planar graph decomposition NeurIPS 2006 Bayesian Detection of Infrequent Differences in Sets of Time Series with Shared Structure NeurIPS 2006 Conditional mean field NeurIPS 2006 Data Integration for Classification Problems Employing Gaussian Process Priors NeurIPS 2006 Estimating the “Wrong” Graphical Model: Benefits in the Computation-Limited Setting JMLR 2006 Modeling Dyadic Data with Binary Latent Factors NeurIPS 2006 Noisy-OR Component Analysis and its Application to Link Analysis JMLR 2006 Parameter Expanded Variational Bayesian Methods NeurIPS 2006 Unified Inference for Variational Bayesian Linear Gaussian State-Space Models NeurIPS 2006 A Unifying View of Sparse Approximate Gaussian Process Regression JMLR 2005 Convergence Theorems for Generalized Alternating Minimization Procedures JMLR 2005 Expectation Consistent Approximate Inference JMLR 2005 Variational Message Passing JMLR 2005 Latent Dirichlet Allocation JMLR 2003