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Tree-structured Gaussian Process Approximations., and . NIPS, page 2213-2221. (2014)Learning Stationary Time Series using Gaussian Processes with Nonparametric Kernels., , and . NIPS, page 3501-3509. (2015)Variational Continual Learning., , , and . ICLR (Poster), OpenReview.net, (2018)Improving and Understanding Variational Continual Learning., , , and . CoRR, (2019)Black-Box Alpha Divergence Minimization., , , , , and . ICML, volume 48 of JMLR Workshop and Conference Proceedings, page 1511-1520. JMLR.org, (2016)Deep Gaussian Processes for Regression using Approximate Expectation Propagation, , , , and . (2016)cite arxiv:1602.04133.Variational Auto-Regressive Gaussian Processes for Continual Learning., , and . ICML, volume 139 of Proceedings of Machine Learning Research, page 5290-5300. PMLR, (2021)Neural Graph Learning: Training Neural Networks Using Graphs., , and . WSDM, page 64-71. ACM, (2018)Partitioned Variational Inference: A unified framework encompassing federated and continual learning., , , and . CoRR, (2018)A Unifying Framework for Gaussian Process Pseudo-Point Approximations using Power Expectation Propagation, , and . (2016)cite arxiv:1605.07066.