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Variational Inference

1946 directly classified papers

Papers per year

Papers

Kullback-Leibler Proximal Variational Inference NIPS 2015
Variational Inference for Gaussian Process Modulated Poisson Processes ICML 2015
Probabilistic Backpropagation for Scalable Learning of Bayesian Neural Networks ICML 2015
Condition for Perfect Dimensionality Recovery by Variational Bayesian PCA JMLR 2015
Copula variational inference NIPS 2015
Fast Second Order Stochastic Backpropagation for Variational Inference NIPS 2015
Celeste: Variational inference for a generative model of astronomical images ICML 2015
Analysis of Variational Bayesian Latent Dirichlet Allocation: Weaker Sparsity Than MAP NIPS 2014
Improved Multimodal Deep Learning with Variation of Information NIPS 2014
Decoupled Variational Gaussian Inference NIPS 2014
A Complete Variational Tracker NIPS 2014
Neural Variational Inference and Learning in Belief Networks ICML 2014
Variational Gaussian Inference for Bilinear Models of Count Data ACML 2014
Black Box Variational Inference AISTATS 2014
Efficient Gradient-Based Inference through Transformations between Bayes Nets and Neural Nets ICML 2014
Doubly Stochastic Variational Bayes for non-Conjugate Inference ICML 2014
Stochastic Backpropagation and Approximate Inference in Deep Generative Models ICML 2014
Automated Variational Inference for Gaussian Process Models NIPS 2014
Integrated Non-Factorized Variational Inference NIPS 2013
Global Analytic Solution of Fully-observed Variational Bayesian Matrix Factorization JMLR 2013
Stochastic Variational Inference JMLR 2013
Global Solver and Its Efficient Approximation for Variational Bayesian Low-rank Subspace Clustering NIPS 2013
Stochastic Gradient Riemannian Langevin Dynamics on the Probability Simplex NIPS 2013
Multi-Prediction Deep Boltzmann Machines NIPS 2013
Structural Expectation Propagation (SEP): Bayesian structure learning for networks with latent variables AISTATS 2013