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Rates of Convergence for Sparse Variational Gaussian Process Regression

, , and . Proceedings of the 36th International Conference on Machine Learning, volume 97 of Proceedings of Machine Learning Research, page 862--871. Long Beach, California, USA, PMLR, (09--15 Jun 2019)

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Rates of Convergence for Sparse Variational Gaussian Process Regression, , and . Proceedings of the 36th International Conference on Machine Learning, volume 97 of Proceedings of Machine Learning Research, page 862--871. Long Beach, California, USA, PMLR, (09--15 Jun 2019)The ARKdb: genome databases for farmed and other animals., , , , , , , , , and 1 other author(s). Nucleic Acids Res., 29 (1): 106-110 (2001)Wide Mean-Field Bayesian Neural Networks Ignore the Data., , , , and . AISTATS, volume 151 of Proceedings of Machine Learning Research, page 5276-5333. PMLR, (2022)Tighter Bounds on the Log Marginal Likelihood of Gaussian Process Regression Using Conjugate Gradients., , and . ICML, volume 139 of Proceedings of Machine Learning Research, page 362-372. PMLR, (2021)Pathologies of Factorised Gaussian and MC Dropout Posteriors in Bayesian Neural Networks, , , and . (2019)cite arxiv:1909.00719.Bandit optimisation of functions in the Matérn kernel RKHS., , and . AISTATS, volume 108 of Proceedings of Machine Learning Research, page 2486-2495. PMLR, (2020)Convergence of Sparse Variational Inference in Gaussian Processes Regression., , and . J. Mach. Learn. Res., (2020)World class supply management, , and . McGraw-Hill/Irwin, Boston, Mass. u.a., 7. ed edition, (2003)Understanding Variational Inference in Function-Space., , , and . CoRR, (2020)Numerically Stable Sparse Gaussian Processes via Minimum Separation using Cover Trees., , , , , , and . J. Mach. Learn. Res., (2024)