Variational Inference

Variational Message Passing with Structured Inference Networks ICLR 2018 Wasserstein Variational Inference NeurIPS 2018 A Generative Parser with a Discriminative Recognition Algorithm ACL 2017 Collapsed variational Bayes for Markov jump processes NeurIPS 2017 Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms AISTATS 2017 Robust Energy Minimization for BRDF-Invariant Shape From Light Fields CVPR 2017 Stein Variational Gradient Descent as Gradient Flow NeurIPS 2017 Variational Inference via χ Upper Bound Minimization NeurIPS 2017 A Field Model for Repairing 3D Shapes CVPR 2016 A Theoretically Grounded Application of Dropout in Recurrent Neural Networks NeurIPS 2016 Attend, Infer, Repeat: Fast Scene Understanding with Generative Models NeurIPS 2016 Finite-Dimensional BFRY Priors and Variational Bayesian Inference for Power Law Models NeurIPS 2016 Iterative Refinement of the Approximate Posterior for Directed Belief Networks NeurIPS 2016 Neurally-Guided Procedural Models: Amortized Inference for Procedural Graphics Programs using Neural Networks NeurIPS 2016 Sequential Neural Models with Stochastic Layers NeurIPS 2016 Using Social Dynamics to Make Individual Predictions: Variational Inference with a Stochastic Kinetic Model NeurIPS 2016 Variational Bayes on Monte Carlo Steroids NeurIPS 2016 Automatic Variational Inference in Stan NeurIPS 2015 Barrier Frank-Wolfe for Marginal Inference NeurIPS 2015 Copula variational inference NeurIPS 2015 Decomposition Bounds for Marginal MAP NeurIPS 2015 Deep Convolutional Inverse Graphics Network NeurIPS 2015 Deep Temporal Sigmoid Belief Networks for Sequence Modeling NeurIPS 2015 Fast Second Order Stochastic Backpropagation for Variational Inference NeurIPS 2015 Learning Deep Sigmoid Belief Networks with Data Augmentation AISTATS 2015