variational inference

Latent Intention Dialogue Models ICML 2017 Latent Variable Dialogue Models and their Diversity EACL 2017 Learning Deep Latent Gaussian Models with Markov Chain Monte Carlo ICML 2017 Learning Diverse Image Colorization CVPR 2017 Learning Structured Weight Uncertainty in Bayesian Neural Networks AISTATS 2017 Model-based Bayesian inference of neural activity and connectivity from all-optical interrogation of a neural circuit NeurIPS 2017 Multi-Modal Mean-Fields via Cardinality-Based Clamping CVPR 2017 Multiple Clustering Views from Multiple Uncertain Experts ICML 2017 Multiplicative Normalizing Flows for Variational Bayesian Neural Networks ICML 2017 Multi-space Variational Encoder-Decoders for Semi-supervised Labeled Sequence Transduction ACL 2017 Neural Variational Inference and Learning in Undirected Graphical Models NeurIPS 2017 Non-parametric Structured Output Networks NeurIPS 2017 On the Hyperprior Choice for the Global Shrinkage Parameter in the Horseshoe Prior AISTATS 2017 Perturbative Black Box Variational Inference NeurIPS 2017 Probabilistic Models for Integration Error in the Assessment of Functional Cardiac Models NeurIPS 2017 Reinforcement Learning with Deep Energy-Based Policies ICML 2017 Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms AISTATS 2017 Robust Asymmetric Bayesian Adaptive Matrix Factorization IJCAI 2017 Scalable Model Selection for Belief Networks NeurIPS 2017 Scalable Variational Inference for Dynamical Systems NeurIPS 2017 Scalable Variational Inference for Super Resolution Microscopy AISTATS 2017 ShapeOdds: Variational Bayesian Learning of Generative Shape Models CVPR 2017 Speech Enhancement Using Bayesian Wavenet Interspeech 2017 Stacked Generative Adversarial Networks CVPR 2017 Stein Variational Gradient Descent as Gradient Flow NeurIPS 2017