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Variational Inference

767 directly classified papers

Papers per year

Papers

MCMC for Variationally Sparse Gaussian Processes NIPS 2015
Reweighted Laplace Prior Based Hyperspectral Compressive Sensing for Unknown Sparsity CVPR 2015
Bayesian Inference for Neighborhood Filters With Application in Denoising CVPR 2015
Bayesian Adaptive Matrix Factorization With Automatic Model Selection CVPR 2015
Tilted Variational Bayes AISTATS 2014
Scalable Variational Bayesian Matrix Factorization with Side Information AISTATS 2014
Expectation Propagation for Likelihoods Depending on an Inner Product of Two Multivariate Random Variables AISTATS 2014
Fast Allocation of Gaussian Process Experts ICML 2014
Robust Principal Component Analysis with Complex Noise ICML 2014
Variational Gaussian Process State-Space Models NIPS 2014
Decoupled Variational Gaussian Inference NIPS 2014
Black Box Variational Inference AISTATS 2014
Improved Multimodal Deep Learning with Variation of Information NIPS 2014
On Prior Distributions and Approximate Inference for Structured Variables NIPS 2014
From MAP to Marginals: Variational Inference in Bayesian Submodular Models NIPS 2014
Automated Variational Inference for Gaussian Process Models NIPS 2014
Stochastic variational inference for hidden Markov models NIPS 2014
Extended and Unscented Gaussian Processes NIPS 2014
Approximate Slice Sampling for Bayesian Posterior Inference AISTATS 2014
A Bayesian model for identifying hierarchically organised states in neural population activity NIPS 2014
Analysis of Variational Bayesian Latent Dirichlet Allocation: Weaker Sparsity Than MAP NIPS 2014
Analysis of Empirical MAP and Empirical Partially Bayes: Can They be Alternatives to Variational Bayes? AISTATS 2014
A Complete Variational Tracker NIPS 2014
Concavity of reweighted Kikuchi approximation NIPS 2014
Smoothed Gradients for Stochastic Variational Inference NIPS 2014