Variational Inference

Mixture of Bilateral-Projection Two-Dimensional Probabilistic Principal Component Analysis CVPR 2016 Relevant sparse codes with variational information bottleneck NeurIPS 2016 Rényi Divergence Variational Inference NeurIPS 2016 Scaling Factorial Hidden Markov Models: Stochastic Variational Inference without Messages NeurIPS 2016 Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm NeurIPS 2016 Stochastic Variational Inference for the HDP-HMM AISTATS 2016 Tight Variational Bounds via Random Projections and I-Projections AISTATS 2016 Variance Reduction in Stochastic Gradient Langevin Dynamics NeurIPS 2016 Variational Bayes on Monte Carlo Steroids NeurIPS 2016 Variational Inference in Mixed Probabilistic Submodular Models NeurIPS 2016 Variational Tempering AISTATS 2016 Accurate and conservative estimates of MRF log-likelihood using reverse annealing AISTATS 2015 A Hybrid Approach for Probabilistic Inference using Random Projections ICML 2015 A Recurrent Latent Variable Model for Sequential Data NeurIPS 2015 Automatic Variational Inference in Stan NeurIPS 2015 Barrier Frank-Wolfe for Marginal Inference NeurIPS 2015 Bayesian Adaptive Matrix Factorization With Automatic Model Selection CVPR 2015 Bayesian Inference for Neighborhood Filters With Application in Denoising CVPR 2015 Bayesian Manifold Learning: The Locally Linear Latent Variable Model (LL-LVM) NeurIPS 2015 Bounding errors of Expectation-Propagation NeurIPS 2015 Copula variational inference NeurIPS 2015 Deep Poisson Factor Modeling NeurIPS 2015 Deep Temporal Sigmoid Belief Networks for Sequence Modeling NeurIPS 2015 Expectation Particle Belief Propagation NeurIPS 2015 Fast Second Order Stochastic Backpropagation for Variational Inference NeurIPS 2015