2 papers
cs.LG2026
Enhancing Physics-Informed Neural Networks with Domain-aware Fourier Features: Towards Improved Performance and Interpretable Results
Alberto Miño Calero, Luis Salamanca, Konstantinos E. Tatsis
Physics-Informed Neural Networks (PINNs) incorporate physics into neural networks by embedding partial differential equations (PDEs) into their loss function. Despite their success…
cs.CE2025
Graph Neural Network-Based Predictive Modeling for Robotic Plaster Printing
Diego Machain Rivera, Selen Ercan Jenny, Ping Hsun Tsai +4
This work proposes a Graph Neural Network (GNN) modeling approach to predict the resulting surface from a particle based fabrication process. The latter consists of spray-based pri…