The Gaussian Neural Process

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On sparse variational methods and the Kullback-Leibler divergence between stochastic processes

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Functional variational Bayesian neural networks

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Universal approximations of invariant maps by neural networks

Original

D. Yarotsky · 2018

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Attentive neural processes

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Scalable training of inference networks for Gaussian-process models

J. Shi, M. Emtiyaz Khan, and J. Zhu · 2019

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Meta-learning stationary stochastic process prediction with convolutional neural processes

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Convolutional conditional neural processes

Jonathan Gordon, Wessel P. Bruinsma, Andrew Y. K. Foong, James Requeima, Yann Dubois, and Richard E. Turner · 2020

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