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Probabilistic Backpropagation for Scalable Learning of Bayesian Neural Networks., and . ICML, volume 37 of JMLR Workshop and Conference Proceedings, page 1861-1869. JMLR.org, (2015)A Probabilistic Model for Dirty Multi-task Feature Selection., , and . ICML, volume 37 of JMLR Workshop and Conference Proceedings, page 1073-1082. JMLR.org, (2015)Dynamic Covariance Models for Multivariate Financial Time Series., , and . ICML (3), volume 28 of JMLR Workshop and Conference Proceedings, page 558-566. JMLR.org, (2013)Competitive and Collaborative Mixtures of Experts for Financial Risk Analysis., and . ICANN (2), volume 4132 of Lecture Notes in Computer Science, page 691-700. Springer, (2006)Expectation Propagation for Bayesian Multi-task Feature Selection., , , and . ECML/PKDD (1), volume 6321 of Lecture Notes in Computer Science, page 522-537. Springer, (2010)Deep Gaussian Processes for Regression using Approximate Expectation Propagation, , , , and . (2016)cite arxiv:1602.04133.Generating Molecules via Chemical Reactions., , , , and . DGS@ICLR, OpenReview.net, (2019)Deterministic Variational Inference for Robust Bayesian Neural Networks., , , , , and . ICLR, OpenReview.net, (2019)Variational Depth Search in ResNets., , and . CoRR, (2020)Introducing instance label correlation in multiple instance learning. Application to cancer detection on histopathological images., , , and . CoRR, (2023)