variational inference

STCN: Stochastic Temporal Convolutional Networks ICLR 2019 Stein Variational Gradient Descent With Matrix-Valued Kernels NeurIPS 2019 Stochastic Filter Groups for Multi-Task CNNs: Learning Specialist and Generalist Convolution Kernels ICCV 2019 Stochastic Prediction of Multi-Agent Interactions from Partial Observations ICLR 2019 Stochastic Wasserstein Autoencoder for Probabilistic Sentence Generation NAACL 2019 Structured Neural Topic Models for Reviews AISTATS 2019 Structured Variational Inference in Continuous Cox Process Models NeurIPS 2019 Subspace Inference for Bayesian Deep Learning UAI 2019 Switching Linear Dynamics for Variational Bayes Filtering ICML 2019 Tensor Monte Carlo: Particle Methods for the GPU era NeurIPS 2019 The continuous Bernoulli: fixing a pervasive error in variational autoencoders NeurIPS 2019 The Deep Weight Prior ICLR 2019 The LORACs Prior for VAEs: Letting the Trees Speak for the Data AISTATS 2019 Theoretical guarantees for sampling and inference in generative models with latent diffusions COLT 2019 The Thermodynamic Variational Objective NeurIPS 2019 The Trajectron: Probabilistic Multi-Agent Trajectory Modeling With Dynamic Spatiotemporal Graphs ICCV 2019 The Variational Predictive Natural Gradient ICML 2019 Topic Modeling with Wasserstein Autoencoders ACL 2019 Trust Region Sequential Variational Inference ACML 2019 Unbiased Implicit Variational Inference AISTATS 2019 Uncertainty Autoencoders: Learning Compressed Representations via Variational Information Maximization AISTATS 2019 Uncertainty-Aware Audiovisual Activity Recognition Using Deep Bayesian Variational Inference ICCV 2019 Uncertainty-based Continual Learning with Adaptive Regularization NeurIPS 2019 Unconstrained Monotonic Neural Networks NeurIPS 2019 uniblock: Scoring and Filtering Corpus with Unicode Block Information EMNLP 2019