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Variational Inference

107 papers

Papers per year

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Papers

Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms AISTATS 2017
Robust Energy Minimization for BRDF-Invariant Shape From Light Fields CVPR 2017
A Theoretically Grounded Application of Dropout in Recurrent Neural Networks NIPS 2016
Finite-Dimensional BFRY Priors and Variational Bayesian Inference for Power Law Models NIPS 2016
Iterative Refinement of the Approximate Posterior for Directed Belief Networks NIPS 2016
Using Social Dynamics to Make Individual Predictions: Variational Inference with a Stochastic Kinetic Model NIPS 2016
A Field Model for Repairing 3D Shapes CVPR 2016
Automatic Variational Inference in Stan NIPS 2015
The Population Posterior and Bayesian Modeling on Streams NIPS 2015
Learning Structured Output Representation using Deep Conditional Generative Models NIPS 2015
Copula variational inference NIPS 2015
Learning Deep Sigmoid Belief Networks with Data Augmentation AISTATS 2015
A Complete Variational Tracker NIPS 2014
Decoupled Variational Gaussian Inference NIPS 2014
Clamping Variables and Approximate Inference NIPS 2014
Stochastic variational inference for hidden Markov models NIPS 2014
Iterative Neural Autoregressive Distribution Estimator NADE-k NIPS 2014
Expectation Backpropagation: Parameter-Free Training of Multilayer Neural Networks with Continuous or Discrete Weights NIPS 2014
From MAP to Marginals: Variational Inference in Bayesian Submodular Models NIPS 2014
Multi-Prediction Deep Boltzmann Machines NIPS 2013
Learning to Pass Expectation Propagation Messages NIPS 2013
Integrated Non-Factorized Variational Inference NIPS 2013
Demixing odors - fast inference in olfaction NIPS 2013
Approximate inference in latent Gaussian-Markov models from continuous time observations NIPS 2013
Variational Learning for Recurrent Spiking Networks NIPS 2011