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Stable ResNet

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arxiv 2010.12859 v2 pith:Z7WB2ECR submitted 2020-10-24 cs.LG stat.ML

Stable ResNet

classification cs.LG stat.ML
keywords resnetdepthgradientarchitecturesexpressivitymightstablethey
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Deep ResNet architectures have achieved state of the art performance on many tasks. While they solve the problem of gradient vanishing, they might suffer from gradient exploding as the depth becomes large (Yang et al. 2017). Moreover, recent results have shown that ResNet might lose expressivity as the depth goes to infinity (Yang et al. 2017, Hayou et al. 2019). To resolve these issues, we introduce a new class of ResNet architectures, called Stable ResNet, that have the property of stabilizing the gradient while ensuring expressivity in the infinite depth limit.

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