13 citations · 13 across the 4 of their papers we have counts for
4 papers
AURA: Angular Update Rate Adaptation for training complex-valued neural networks
Enrico Ballini, Allan Peter Engsig-Karup, Tito Andriollo
Complex-valued neural networks (CVNNs) are increasingly adopted for complex-valued data; however, they are often trained with first-order optimizers inherited from the real-valued…
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…
A holomorphic Kolmogorov-Arnold network framework for solving elliptic problems on arbitrary 2D domains
Matteo Calafà, 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…
Physics-Informed Holomorphic Neural Networks (PIHNNs): Solving Linear Elasticity Problems
Matteo Calafà, Emil Hovad, Allan P. Engsig-Karup +1
We propose physics-informed holomorphic neural networks (PIHNNs) as a method to solve boundary value problems where the solution can be represented via holomorphic functions. Speci…