Variational Inference

Decoupled Variational Gaussian Inference NeurIPS 2014 Doubly Stochastic Variational Bayes for non-Conjugate Inference ICML 2014 Efficient Gradient-Based Inference through Transformations between Bayes Nets and Neural Nets ICML 2014 Improved Multimodal Deep Learning with Variation of Information NeurIPS 2014 Iterative Neural Autoregressive Distribution Estimator NADE-k NeurIPS 2014 Neural Variational Inference and Learning in Belief Networks ICML 2014 Stochastic Backpropagation and Approximate Inference in Deep Generative Models ICML 2014 Variational Gaussian Inference for Bilinear Models of Count Data ACML 2014 An Optimal Policy for Target Localization with Application to Electron Microscopy ICML 2013 Approximate Bayesian Image Interpretation using Generative Probabilistic Graphics Programs NeurIPS 2013 Approximate inference in latent Gaussian-Markov models from continuous time observations NeurIPS 2013 A Scalable Approach to Probabilistic Latent Space Inference of Large-Scale Networks NeurIPS 2013 Bayesian Canonical Correlation Analysis JMLR 2013 Dense Variational Reconstruction of Non-rigid Surfaces from Monocular Video CVPR 2013 Global Analytic Solution of Fully-observed Variational Bayesian Matrix Factorization JMLR 2013 Global Solver and Its Efficient Approximation for Variational Bayesian Low-rank Subspace Clustering NeurIPS 2013 Integrated Non-Factorized Variational Inference NeurIPS 2013 Memoized Online Variational Inference for Dirichlet Process Mixture Models NeurIPS 2013 Multi-image Blind Deblurring Using a Coupled Adaptive Sparse Prior CVPR 2013 Multi-Prediction Deep Boltzmann Machines NeurIPS 2013 Probabilistic Principal Geodesic Analysis NeurIPS 2013 Stochastic Gradient Riemannian Langevin Dynamics on the Probability Simplex NeurIPS 2013 Stochastic Variational Inference JMLR 2013 Structural Expectation Propagation (SEP): Bayesian structure learning for networks with latent variables AISTATS 2013 Affine Independent Variational Inference NeurIPS 2012