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GNet: A scalable and flexible Gaussian process network with nonparametric neurons
We build GNet, a scalable and flexible Gaussian process network with nonparametric activation functions. The key computational contribution is to make estimation of GP activations computationally scalable without forming covariance matrices explicitly. We provide theoretical studies comparing functi
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