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Large-width functional asymptotics for deep Gaussian neural networks
In this paper, we consider fully connected feed-forward deep neural networks where weights and biases are independent and identically distributed according to Gaussian distributions.
Infinite-channel deep stable convolutional neural networks
The interplay between infinite-width neural networks (NNs) and classes of Gaussian processes (GPs) is well known since the seminal work of Neal (1996).
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