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Gaussian processes (GPs) are flexible non-parametric models, with a capacity that grows with the available data.
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A. G. Wilson, D. A. Knowles, and Z. Ghahramani · 2012
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Fastfood: approximating kernel expansions in loglinear time
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K. Dong, D. Eriksson, H. Nickisch, D. Bindel, and A. G. Wilson · 2017
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Gpflow: A gaussian process library using tensorflow
A. G. d. G. Matthews, M. van der Wilk, T. Nickson, K. Fujii, A. Boukouvalas, P. León-Villagrá, Z. Ghahramani, and J. Hensman · 2017
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Doubly stochastic variational inference for deep gaussian processes
H. Salimbeni and M. Deisenroth · 2017
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Constant-time predictive distributions for gaussian processes
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Orthogonally decoupled variational gaussian processes
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