EF1 – Extracting Dynamical Laws from Complex Data



On robustness of deep neural networks

Project Heads

Christian Bayer, Peter Friz

Project Members

Nikolas Tapia (TU), Nikolas Tapia (WIAS) 

Project Duration

01.01.2019 – 31.12.2020

Located at

TU Berlin / WIAS


Deep residual neural networks [He, Zhang, Ren, Sun 2016] are an important recent class of deep neural networks. Its incremental nature invites interpretation as Euler discretization of differential equations [Haber and Ruthotto 2017]. We suggest a far-reaching generalization using signatures and rough path analysis.

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