State Space Representations of Deep Neural Networks

doi:doi:10.57702/z74wuci9

State Space Representations of Deep Neural Networks

This paper deals with neural networks as dynamical systems governed by finite difference equations. It shows that the introduction of k-many skip connections into network architectures, such as residual networks and additive dense networks, define kth order dynamical equations on the layer-wise transformations.

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Michael Hauser, Sean Gunn, Samer Saab Jr, Asok Ray (2024). Dataset: State Space Representations of Deep Neural Networks. https://doi.org/10.57702/z74wuci9

DOI retrieved: December 16, 2024

Additional Info

Field	Value
Created	December 16, 2024
Last update	December 16, 2024
Defined In	https://doi.org/10.1162/neco_a_01165
Author	Michael Hauser
More Authors	Sean Gunn Samer Saab Jr Asok Ray