Physics-informed neural networks for severe weather event prediction
The novel development of Physics-Informed Neural Networks (PINNs), which incorporate the constraints given by physics laws into the training process, as an excellent means of computing fluidic fields and their characteristics such as velocity and pressure, has opened the gates to numerous applications. One of them is the data enhancement of experiments, since PINNs can reconstruct by means of applying the Navier-Stokes equations as loss function the full fluid domain in areas where experiments are limited by technology.
MSCA PERSEVERE 