Variational Inference

Minimal Random Code Learning: Getting Bits Back from Compressed Model Parameters ICLR 2019 MIWAE: Deep Generative Modelling and Imputation of Incomplete Data Sets ICML 2019 Modeling Event Background for If-Then Commonsense Reasoning Using Context-aware Variational Autoencoder EMNLP 2019 Modeling Personalization in Continuous Space for Response Generation via Augmented Wasserstein Autoencoders EMNLP 2019 Modeling the Long Term Future in Model-Based Reinforcement Learning ICLR 2019 Molecular Hypergraph Grammar with Its Application to Molecular Optimization ICML 2019 Moment-Based Variational Inference for Markov Jump Processes ICML 2019 Multi-Angle Point Cloud-VAE: Unsupervised Feature Learning for 3D Point Clouds From Multiple Angles by Joint Self-Reconstruction and Half-to-Half Prediction ICCV 2019 Multi-Granularity Representations of Dialog EMNLP 2019 Multi-Object Representation Learning with Iterative Variational Inference ICML 2019 Multi-objects Generation with Amortized Structural Regularization NeurIPS 2019 Multi-Source Neural Variational Inference AAAI 2019 Neural Gaussian Copula for Variational Autoencoder EMNLP 2019 Neural Probabilistic Motor Primitives for Humanoid Control ICLR 2019 Neural Spline Flows NeurIPS 2019 Neural Topic Model with Reinforcement Learning EMNLP 2019 NeVAE: A Deep Generative Model for Molecular Graphs AAAI 2019 ODE2VAE: Deep generative second order ODEs with Bayesian neural networks NeurIPS 2019 On the Importance of the Kullback-Leibler Divergence Term in Variational Autoencoders for Text Generation EMNLP 2019 On Variational Bounds of Mutual Information ICML 2019 Optimal Transport Maps For Distribution Preserving Operations on Latent Spaces of Generative Models ICLR 2019 Overcoming Mean-Field Approximations in Recurrent Gaussian Process Models ICML 2019 Path-Specific Counterfactual Fairness AAAI 2019 Pathwise Derivatives for Multivariate Distributions AISTATS 2019 Pluralistic Image Completion CVPR 2019