2 citations · 3 across the 4 of their papers we have counts for
4 papers
Simulating the aftermath of Northern European Enclosure Dam (NEED) break and flooding of European coast
Paweł Maczuga, Marcin Łoś, Eirik Valseth +5
The Northern European Enclosure Dam (NEED) is a hypothetical project to prevent flooding in European countries following the rising ocean level due to melting arctic glaciers. This…
Collocation-based Robust Variational Physics-Informed Neural Networks (CRVPINN)
Marcin Łoś, Tomasz Służalec, Paweł Maczuga +3
Physics-Informed Neural Networks (PINNs) have been successfully applied to solve Partial Differential Equations (PDEs). Their loss function is founded on a strong residual minimiza…
Physics Informed Neural Network Code for 2D Transient Problems (PINN-2DT) Compatible with Google Colab
Paweł Maczuga, Maciej Sikora, Maciej Skoczeń +7
We present an open-source Physics Informed Neural Network environment for simulations of transient phenomena on two-dimensional rectangular domains, with the following features: (1…
Robust Variational Physics-Informed Neural Networks
Sergio Rojas, Paweł Maczuga, Judit Muñoz-Matute +2
We introduce a Robust version of the Variational Physics-Informed Neural Networks method (RVPINNs). As in VPINNs, we define the quadratic loss functional in terms of a Petrov-Galer…