2 papers
cs.CE2026
Crack detection by holomorphic neural networks and transfer-learning-enhanced genetic optimization
Jonas Hund, Nicolas Cuenca, Tito Andriollo
A physics-informed machine learning framework based on holomorphic neural networks is introduced for detecting cracks in two-dimensional solids from strain or displacement data. Cr…
cs.CE2025
A holomorphic Kolmogorov-Arnold network framework for solving elliptic problems on arbitrary 2D domains
Matteo CalafÃ, Tito Andriollo, Allan P. Engsig-Karup +1
Physics-informed holomorphic neural networks (PIHNNs) have recently emerged as efficient surrogate models for solving differential problems. By embedding the underlying problem str…