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Variational Inference

767 directly classified papers

Papers per year

Papers

Accurate and conservative estimates of MRF log-likelihood using reverse annealing AISTATS 2015
Regularized EM Algorithms: A Unified Framework and Statistical Guarantees NIPS 2015
Scalable Variational Gaussian Process Classification AISTATS 2015
Deep Temporal Sigmoid Belief Networks for Sequence Modeling NIPS 2015
Stochastic Structured Variational Inference AISTATS 2015
Reliable and Scalable Variational Inference for the Hierarchical Dirichlet Process AISTATS 2015
Learning Stationary Time Series using Gaussian Processes with Nonparametric Kernels NIPS 2015
Neural Adaptive Sequential Monte Carlo NIPS 2015
Expectation Particle Belief Propagation NIPS 2015
Optimization Monte Carlo: Efficient and Embarrassingly Parallel Likelihood-Free Inference NIPS 2015
Variational Dropout and the Local Reparameterization Trick NIPS 2015
Low-Rank Matrix Factorization Under General Mixture Noise Distributions ICCV 2015
Bayesian Manifold Learning: The Locally Linear Latent Variable Model (LL-LVM) NIPS 2015
Variational Information Maximisation for Intrinsically Motivated Reinforcement Learning NIPS 2015
Copula variational inference NIPS 2015
Variational Consensus Monte Carlo NIPS 2015
Fast Second Order Stochastic Backpropagation for Variational Inference NIPS 2015
Barrier Frank-Wolfe for Marginal Inference NIPS 2015
Local Expectation Gradients for Black Box Variational Inference NIPS 2015
Kullback-Leibler Proximal Variational Inference NIPS 2015
Automatic Variational Inference in Stan NIPS 2015
A Hybrid Approach for Probabilistic Inference using Random Projections ICML 2015
Streaming, Distributed Variational Inference for Bayesian Nonparametrics NIPS 2015
Scalable Inference for Gaussian Process Models with Black-Box Likelihoods NIPS 2015
Bounding errors of Expectation-Propagation NIPS 2015