Wide Neural Networks with Bottlenecks are Deep Gaussian Processes

3 Jan 2020Devanshu AgrawalTheodore PapamarkouJacob Hinkle

There has recently been much work on the "wide limit" of neural networks, where Bayesian neural networks (BNNs) are shown to converge to a Gaussian process (GP) as all hidden layers are sent to infinite width. However, these results do not apply to architectures that require one or more of the hidden layers to remain narrow... (read more)

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