Variational Inference

Rényi Divergence Variational Inference NeurIPS 2016 Scaling Factorial Hidden Markov Models: Stochastic Variational Inference without Messages NeurIPS 2016 Sequential Neural Models with Stochastic Layers NeurIPS 2016 Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm NeurIPS 2016 Stochastic Variational Deep Kernel Learning NeurIPS 2016 Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteriors ICML 2016 The Generalized Reparameterization Gradient NeurIPS 2016 Tight Variational Bounds via Random Projections and I-Projections AISTATS 2016 Variational Autoencoder for Deep Learning of Images, Labels and Captions NeurIPS 2016 Variational Bayes on Monte Carlo Steroids NeurIPS 2016 Variational Dependent Multi-output Gaussian Process Dynamical Systems JMLR 2016 Variational Inference for Latent Variables and Uncertain Inputs in Gaussian Processes JMLR 2016 Variational Inference for Monte Carlo Objectives ICML 2016 Variational Inference in Mixed Probabilistic Submodular Models NeurIPS 2016 Variational Tempering AISTATS 2016 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 Bounding errors of Expectation-Propagation NeurIPS 2015 Celeste: Variational inference for a generative model of astronomical images ICML 2015 Condition for Perfect Dimensionality Recovery by Variational Bayesian PCA JMLR 2015 Copula variational inference NeurIPS 2015 DRAW: A Recurrent Neural Network For Image Generation ICML 2015 Efficient Minimal-Surface Regularization of Perspective Depth Maps in Variational Stereo CVPR 2015 Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images NeurIPS 2015