Variational Inference

Discovering Weakly-Interacting Factors in a Complex Stochastic Process NeurIPS 2007 Fast Variational Inference for Large-scale Internet Diagnosis NeurIPS 2007 Loop Series and Bethe Variational Bounds in Attractive Graphical Models NeurIPS 2007 Neural characterization in partially observed populations of spiking neurons NeurIPS 2007 New Outer Bounds on the Marginal Polytope NeurIPS 2007 Robust Regression with Twinned Gaussian Processes 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 A Novel Gaussian Sum Smoother for Approximate Inference in Switching Linear Dynamical Systems 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 Expectation Correction for Smoothed Inference in Switching Linear Dynamical Systems JMLR 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 Assessing Approximate Inference for Binary Gaussian Process Classification JMLR 2005 Convergence Theorems for Generalized Alternating Minimization Procedures JMLR 2005 Expectation Consistent Approximate Inference JMLR 2005 An Approximate Analytical Approach to Resampling Averages JMLR 2003