13 citations · 13 across the 5 of their papers we have counts for
5 papers
Surface impedance inference via neural fields and sparse acoustic data obtained by a compact array
Yuanxin Xia, Xinyan Li, Matteo Calafà +2
Standardized laboratory characterizations for absorbing materials rely on idealized sound field assumptions, which deviate largely from real-life conditions. Consequently, \emph{in…
Evaluation of acoustic Green's function in rectangular rooms with general surface impedance walls
Matteo Calafà, Yuanxin Xia, Jonas Brunskog +1
Acoustic room modes admit closed-form expressions for rectangular rooms with perfectly reflecting walls, from which the Green's function can be computed directly through the eigenf…
HergNet: a Fast Neural Surrogate Model for Sound Field Predictions via Superposition of Plane Waves
Matteo Calafà, Yuanxin Xia, Cheol-Ho Jeong
We present a novel neural network architecture for the efficient prediction of sound fields in two and three dimensions. The network is designed to automatically satisfy the Helmho…
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…