- New Environment Test
Succeeded with Mac M1 with TensorFlow=2.13, GPflow=2.2;
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Trials
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whiten=True;
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Identity mean function at the final layer;
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identity prior mean function for inducing inputs
$\mathbf{Z}^{(l-1)}$ at the$l$ -th intermediate layer, whose form is the same as the prior mean of outputs$\mathbf{F}^{(l)}: \mathbb{E}[\mathbf{F}^{(l)}] = m(\mathbf{F}^{(l-1)})=\mathbf{F}^{(l-1)}$ .
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from the forked:
🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow 2.0 and TensorFlow 2.0.
Heavily based on a previous implementation of Doubly-Stochastic-DGP and the paper
@inproceedings{salimbeni2017doubly,
title={Doubly stochastic variational inference for deep gaussian processes},
author={Salimbeni, Hugh and Deisenroth, Marc},
booktitle={Advances in Neural Information Processing Systems},
year={2017}
}
Includes demos for the step function and MNIST data set.