Robustness and generalization performance of Deep Learning Models on Cyber-Physical Systems

In this episode, Peter Seeberg talks to Prof. Dr. Oliver Niggemann about his study Robustness and Generalization Performance of Deep Learning Models on Cyber-Physical Systems. Deep learning (DL) models have seen increased attention for time series forecasting, yet the application on cyber-physical systems (CPS) is hindered by the lacking robustness of these methods. Thus, this study evaluates the robustness and generalization performance of DL architectures on multivariate time series data from CPS. 

Shownotes:

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