Bayesian & Probabilistic

Stagewise Safe Bayesian Optimization with Gaussian Processes ICML 2018 State-by-state Minimax Adaptive Estimation for Nonparametric Hidden {M}arkov Models JMLR 2018 State Space Gaussian Processes with Non-Gaussian Likelihood ICML 2018 Stein Variational Gradient Descent Without Gradient ICML 2018 Stein Variational Message Passing for Continuous Graphical Models ICML 2018 Stochastic Wasserstein Barycenters ICML 2018 Stock Movement Prediction from Tweets and Historical Prices ACL 2018 Structured Gaussian Processes with Twin Multiple Kernel Learning ACML 2018 Structure Learning for Bayesian Networks over Labeled DAGs PGM 2018 Structure Learning Under Missing Data PGM 2018 Sum-Product-Quotient Networks AISTATS 2018 Supervised I-vector Modeling - Theory and Applications Interspeech 2018 Tagging Like Humans: Diverse and Distinct Image Annotation CVPR 2018 Temporal Poisson Square Root Graphical Models ICML 2018 The Hierarchical Adaptive Forgetting Variational Filter ICML 2018 The Importance of Calibration for Estimating Proportions from Annotations NAACL 2018 Theoretical guarantees for EM under misspecified Gaussian mixture models NeurIPS 2018 The promises and pitfalls of Stochastic Gradient Langevin Dynamics NeurIPS 2018 The University of Texas System Submission for the Code-Switching Workshop Shared Task 2018 ACL 2018 Tighter Variational Bounds are Not Necessarily Better ICML 2018 Transfer of Value Functions via Variational Methods NeurIPS 2018 Uncertainty-Aware Attention for Reliable Interpretation and Prediction NeurIPS 2018 Uncovering Causality from Multivariate Hawkes Integrated Cumulants JMLR 2018 Unifying DAGs and UGs PGM 2018 VAE with a VampPrior AISTATS 2018