Author

A. Raptis

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Open access Sep 2026

On the Performance of Physics-Informed Neural Networks for Hemodynamic Predictions in Parameterized Vascular Stenoses

It is highlighted that while current PINNs can reliably reproduce velocity fields, their ability to capture localized pressure dynamics remains limited, indicating the need for more robust formulations.

Michail Athanasiou, A. Raptis, Christos G. Manopoulos · Computation · 0 citations

#reinforcement learning Open access Sep 2026

Dynamic defense strategies for cyber-physical systems using Stackelberg games and deep reinforcement learning in discrete and continuous time

As cyber threats to power grid infrastructures escalate, the urgency of understanding how to protect cyber-physical systems (CPS) has never been greater. These systems, which integrate physical processes with digital control, are increasingly susceptible to sophisticated cyberattacks that can lead to widespread disrupt...

A. Raptis, S. Gritzalis, A. Yannacopoulos · International Journal of Inf... · 0 citations