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Variational Inference

802 papers

Papers per year

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33
100
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Papers

A Theoretically Grounded Application of Dropout in Recurrent Neural Networks NIPS 2016
Variational Bayes on Monte Carlo Steroids NIPS 2016
Iterative Refinement of the Approximate Posterior for Directed Belief Networks NIPS 2016
Disease Trajectory Maps NIPS 2016
Rényi Divergence Variational Inference NIPS 2016
Scaling Factorial Hidden Markov Models: Stochastic Variational Inference without Messages NIPS 2016
Variational Inference in Mixed Probabilistic Submodular Models NIPS 2016
Distributed Flexible Nonlinear Tensor Factorization NIPS 2016
Variance Reduction in Stochastic Gradient Langevin Dynamics NIPS 2016
Relevant sparse codes with variational information bottleneck NIPS 2016
Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm NIPS 2016
Variational Tempering AISTATS 2016
A Fixed-Point Operator for Inference in Variational Bayesian Latent Gaussian Models AISTATS 2016
Stochastic Variational Inference for the HDP-HMM AISTATS 2016
Exponential Stochastic Cellular Automata for Massively Parallel Inference AISTATS 2016
Early Stopping as Nonparametric Variational Inference AISTATS 2016
Tight Variational Bounds via Random Projections and I-Projections AISTATS 2016
Black-Box Policy Search with Probabilistic Programs AISTATS 2016
Learning Sigmoid Belief Networks via Monte Carlo Expectation Maximization AISTATS 2016
Mixture of Bilateral-Projection Two-Dimensional Probabilistic Principal Component Analysis CVPR 2016
Black-Box Alpha Divergence Minimization ICML 2016
Energetic Natural Gradient Descent ICML 2016
A Variational Approach to Path Estimation and Parameter Inference of Hidden Diffusion Processes JMLR 2016
d-VMP: Distributed Variational Message Passing PGM 2016
Barrier Frank-Wolfe for Marginal Inference NIPS 2015