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Variational Inference

1,952 papers

Papers per year

2
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31
252
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Papers

Scaling Factorial Hidden Markov Models: Stochastic Variational Inference without Messages NIPS 2016
Variational Inference in Mixed Probabilistic Submodular Models NIPS 2016
Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm NIPS 2016
Stochastic Variational Deep Kernel Learning NIPS 2016
f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization NIPS 2016
Operator Variational Inference NIPS 2016
Improved Variational Inference with Inverse Autoregressive Flow NIPS 2016
Variational Autoencoder for Deep Learning of Images, Labels and Captions NIPS 2016
The Generalized Reparameterization Gradient NIPS 2016
Clamping Improves TRW and Mean Field Approximations AISTATS 2016
On Sparse Variational Methods and the Kullback-Leibler Divergence between Stochastic Processes AISTATS 2016
Relationship between PreTraining and Maximum Likelihood Estimation in Deep Boltzmann Machines AISTATS 2016
Variational Tempering AISTATS 2016
A Fixed-Point Operator for Inference in Variational Bayesian Latent Gaussian Models AISTATS 2016
Early Stopping as Nonparametric Variational Inference AISTATS 2016
Tight Variational Bounds via Random Projections and I-Projections AISTATS 2016
Deep Gaussian Conditional Random Field Network: A Model-Based Deep Network for Discriminative Denoising CVPR 2016
Hierarchical Variational Models ICML 2016
A Distributed Variational Inference Framework for Unifying Parallel Sparse Gaussian Process Regression Models ICML 2016
Learning to Generate with Memory ICML 2016
Auxiliary Deep Generative Models ICML 2016
Autoencoding beyond pixels using a learned similarity metric ICML 2016
Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteriors ICML 2016
Neural Variational Inference for Text Processing ICML 2016
Variational Inference for Monte Carlo Objectives ICML 2016