Variational Inference

Variational bounds for mixed-data factor analysis NeurIPS 2010 Variational Inference over Combinatorial Spaces NeurIPS 2010 Variational methods for Reinforcement Learning AISTATS 2010 A Bayesian Model for Simultaneous Image Clustering, Annotation and Object Segmentation NeurIPS 2009 A Stochastic approximation method for inference in probabilistic graphical models NeurIPS 2009 Gaussian process regression with Student-t likelihood NeurIPS 2009 Graph Zeta Function in the Bethe Free Energy and Loopy Belief Propagation NeurIPS 2009 Inter-domain Gaussian Processes for Sparse Inference using Inducing Features NeurIPS 2009 Parallel Inference for Latent Dirichlet Allocation on Graphics Processing Units NeurIPS 2009 Particle-based Variational Inference for Continuous Systems NeurIPS 2009 Posterior vs Parameter Sparsity in Latent Variable Models NeurIPS 2009 Variational Gaussian-process factor analysis for modeling spatio-temporal data NeurIPS 2009 Variational Inference for the Nested Chinese Restaurant Process NeurIPS 2009 Bayesian Kernel Shaping for Learning Control NeurIPS 2008 Evaluating probabilities under high-dimensional latent variable models NeurIPS 2008 Extracting State Transition Dynamics from Multiple Spike Trains with Correlated Poisson HMM NeurIPS 2008 Gates NeurIPS 2008 Improving on Expectation Propagation NeurIPS 2008 Relative Performance Guarantees for Approximate Inference in Latent Dirichlet Allocation NeurIPS 2008 Sparse probabilistic projections NeurIPS 2008 Syntactic Topic Models NeurIPS 2008 Using Bayesian Dynamical Systems for Motion Template Libraries NeurIPS 2008 Variational Mixture of Gaussian Process Experts NeurIPS 2008 Collapsed Variational Inference for HDP NeurIPS 2007 Convex Relaxations of Latent Variable Training NeurIPS 2007