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Variational Inference

767 directly classified papers

Papers per year

Papers

A Filtering Approach to Stochastic Variational Inference NIPS 2014
Semi-supervised Learning with Deep Generative Models NIPS 2014
Expectation Backpropagation: Parameter-Free Training of Multilayer Neural Networks with Continuous or Discrete Weights NIPS 2014
Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models NIPS 2014
Variance Reduction for Stochastic Gradient Optimization NIPS 2013
Approximate inference in latent Gaussian-Markov models from continuous time observations NIPS 2013
Structural Expectation Propagation (SEP): Bayesian structure learning for networks with latent variables AISTATS 2013
Smooth Operators ICML 2013
Fast Dual Variational Inference for Non-Conjugate Latent Gaussian Models ICML 2013
Kernelized Bayesian Matrix Factorization ICML 2013
Message passing with l1 penalized KL minimization ICML 2013
Gaussian Process Vine Copulas for Multivariate Dependence ICML 2013
Bayesian Canonical Correlation Analysis JMLR 2013
Efficient Online Inference for Bayesian Nonparametric Relational Models NIPS 2013
Stochastic Gradient Riemannian Langevin Dynamics on the Probability Simplex NIPS 2013
Probabilistic Low-Rank Matrix Completion with Adaptive Spectral Regularization Algorithms NIPS 2013
Global Solver and Its Efficient Approximation for Variational Bayesian Low-rank Subspace Clustering NIPS 2013
Annealing between distributions by averaging moments NIPS 2013
Memoized Online Variational Inference for Dirichlet Process Mixture Models NIPS 2013
Integrated Non-Factorized Variational Inference NIPS 2013
Collapsed Variational Bayesian Inference for Hidden Markov Models AISTATS 2013
Efficient Variational Inference for Gaussian Process Regression Networks AISTATS 2013
Variational Inference for Mahalanobis Distance Metrics in Gaussian Process Regression NIPS 2013
Learning to Pass Expectation Propagation Messages NIPS 2013
Streaming Variational Bayes NIPS 2013