variational inference

Latent-Variable Generative Models for Data-Efficient Text Classification EMNLP 2019 Learning Disentangled Representation with Pairwise Independence AAAI 2019 Learning Feature-to-Feature Translator by Alternating Back-Propagation for Generative Zero-Shot Learning ICCV 2019 Learning Flexible Latent Representations via Encapsulated Variational Encoders AAAI 2019 Learning Hawkes Processes from a handful of events NeurIPS 2019 Learning interpretable continuous-time models of latent stochastic dynamical systems ICML 2019 Learning joint lesion and tissue segmentation from task-specific hetero-modal datasets MIDL 2019 Learning Latent Dynamics for Planning from Pixels ICML 2019 Learning Self-Imitating Diverse Policies ICLR 2019 Learning to Decipher Hate Symbols NAACL 2019 Learning to Write Stories with Thematic Consistency and Wording Novelty AAAI 2019 Likelihood-Free Overcomplete ICA and Applications In Causal Discovery NeurIPS 2019 Loss Landscapes of Regularized Linear Autoencoders ICML 2019 Matched Bipartite Block Model with Covariates JMLR 2019 Meta-Learning Probabilistic Inference for Prediction ICLR 2019 Meta Learning with Relational Information for Short Sequences NeurIPS 2019 Minimal Random Code Learning: Getting Bits Back from Compressed Model Parameters ICLR 2019 Minimax Online Prediction of Varying Bernoulli Process under Variational Approximation ACML 2019 MIWAE: Deep Generative Modelling and Imputation of Incomplete Data Sets ICML 2019 Modeling the Long Term Future in Model-Based Reinforcement Learning ICLR 2019 Model Selection in Bayesian Neural Networks via Horseshoe Priors JMLR 2019 Moment-Based Variational Inference for Markov Jump Processes ICML 2019 Multi-Class Gaussian Process Classification Made Conjugate: Efficient Inference via Data Augmentation UAI 2019 Multi-Object Representation Learning with Iterative Variational Inference ICML 2019 Multi-objects Generation with Amortized Structural Regularization NeurIPS 2019