Variational Inference

Smoothing the Geometry of Probabilistic Box Embeddings ICLR 2019 SOM-VAE: Interpretable Discrete Representation Learning on Time Series ICLR 2019 Sparse Multi-Channel Variational Autoencoder for the Joint Analysis of Heterogeneous Data ICML 2019 Stein Variational Gradient Descent With Matrix-Valued Kernels NeurIPS 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 Structuring Latent Spaces for Stylized Response Generation EMNLP 2019 Subspace Inference for Bayesian Deep Learning UAI 2019 SuperVAE: Superpixelwise Variational Autoencoder for Salient Object Detection AAAI 2019 Syntax-Infused Variational Autoencoder for Text Generation ACL 2019 Task-Conditioned Variational Autoencoders for Learning Movement Primitives CoRL 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 LORACs Prior for VAEs: Letting the Trees Speak for the Data AISTATS 2019 The Thermodynamic Variational Objective NeurIPS 2019 The Variational Predictive Natural Gradient ICML 2019 TopicEq: A Joint Topic and Mathematical Equation Model for Scientific Texts AAAI 2019 Topic Modeling with Wasserstein Autoencoders ACL 2019 Towards Generating Long and Coherent Text with Multi-Level Latent Variable Models ACL 2019 Training Data Augmentation for Detecting Adverse Drug Reactions in User-Generated Content EMNLP 2019 Training Variational Autoencoders with Buffered Stochastic Variational Inference AISTATS 2019 Trust Region Sequential Variational Inference ACML 2019 Unbiased Implicit Variational Inference AISTATS 2019