Variational Inference

AMR Parsing as Graph Prediction with Latent Alignment ACL 2018 A Scalable Laplace Approximation for Neural Networks ICLR 2018 A Stochastic Decoder for Neural Machine Translation ACL 2018 A Structured Variational Autoencoder for Contextual Morphological Inflection ACL 2018 Augment and Reduce: Stochastic Inference for Large Categorical Distributions ICML 2018 Auto-Encoding Sequential Monte Carlo ICLR 2018 A Variational U-Net for Conditional Appearance and Shape Generation CVPR 2018 Better Conversations by Modeling, Filtering, and Optimizing for Coherence and Diversity EMNLP 2018 Black-Box Variational Inference for Stochastic Differential Equations ICML 2018 Boosting Black Box Variational Inference NeurIPS 2018 BRUNO: A Deep Recurrent Model for Exchangeable Data NeurIPS 2018 Can clustering scale sublinearly with its clusters? A variational EM acceleration of GMMs and k-means AISTATS 2018 Coherence-Aware Neural Topic Modeling EMNLP 2018 Commonsense Justification for Action Explanation EMNLP 2018 Compressing Neural Networks using the Variational Information Bottleneck ICML 2018 Connections with Robust PCA and the Role of Emergent Sparsity in Variational Autoencoder Models JMLR 2018 Constrained Generation of Semantically Valid Graphs via Regularizing Variational Autoencoders NeurIPS 2018 Constrained Graph Variational Autoencoders for Molecule Design NeurIPS 2018 Constraining the Dynamics of Deep Probabilistic Models ICML 2018 Coupled Variational Bayes via Optimization Embedding NeurIPS 2018 Covariances, Robustness, and Variational Bayes JMLR 2018 Cross-Modal Deep Variational Hand Pose Estimation CVPR 2018 Debiasing Evidence Approximations: On Importance-weighted Autoencoders and Jackknife Variational Inference ICLR 2018 Deep Poisson gamma dynamical systems NeurIPS 2018 Deep Probabilistic Logic: A Unifying Framework for Indirect Supervision EMNLP 2018