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Finite size corrections for neural network Gaussian processes
There has been a recent surge of interest in modeling neural networks (NNs) as Gaussian processes.
PCA of high dimensional random walks with comparison to neural network training
One technique to visualize the training of neural networks is to perform PCA on the parameters over the course of training and to project to the subspace spanned by the first few PCA components.
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