variational inference

On Nesting Monte Carlo Estimators ICML 2018 On Statistical Optimality of Variational Bayes AISTATS 2018 On Unifying Deep Generative Models ICLR 2018 Optimal Submodular Extensions for Marginal Estimation AISTATS 2018 Pathwise Derivatives Beyond the Reparameterization Trick ICML 2018 Point process latent variable models of larval zebrafish behavior NeurIPS 2018 Probabilistic Machine Learning: Models, Algorithms and a Programming Library IJCAI 2018 Probabilistic Model-Agnostic Meta-Learning NeurIPS 2018 Probabilistic Recurrent State-Space Models ICML 2018 Provable Variational Inference for Constrained Log-Submodular Models NeurIPS 2018 Proximity Variational Inference AISTATS 2018 Quasi-Monte Carlo Variational Inference ICML 2018 Redundancy-resistant Generative Hashing for Image Retrieval IJCAI 2018 Reparameterizing the Birkhoff Polytope for Variational Permutation Inference AISTATS 2018 Robust Locally-Linear Controllable Embedding AISTATS 2018 Scalable Factorized Hierarchical Variational Autoencoder Training Interspeech 2018 Scalable Gaussian Processes with Billions of Inducing Inputs via Tensor Train Decomposition AISTATS 2018 Scalable Generalized Dynamic Topic Models AISTATS 2018 Scaling up Data Augmentation MCMC via Calibration JMLR 2018 Scaling up the Automatic Statistician: Scalable Structure Discovery using Gaussian Processes AISTATS 2018 Semi-crowdsourced Clustering with Deep Generative Models NeurIPS 2018 Semi-Supervised Prediction-Constrained Topic Models AISTATS 2018 Simple, Distributed, and Accelerated Probabilistic Programming NeurIPS 2018 SLANG: Fast Structured Covariance Approximations for Bayesian Deep Learning with Natural Gradient NeurIPS 2018 State Space Gaussian Processes with Non-Gaussian Likelihood ICML 2018