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20182021
most citedUsing activation histograms to bound the number of affine regions in ReLU feed-forward neural networks

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stat.ML2018

A Framework for the construction of upper bounds on the number of affine linear regions of ReLU feed-forward neural networks

Peter Hinz, Sara van de Geer

We present a framework to derive upper bounds on the number of regions that feed-forward neural networks with ReLU activation functions are affine linear on. It is based on an indu…