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Sound Field Reconstruction Using Physics-Informed Boundary Integral Networks

This repository contains the code for the paper:

S. Damiano and T. van Waterschoot, "Sound Field Reconstruction Using Physics-Informed Boundary Integral Networks", in Proceedings of the 33rd European Signal Processing Conference (EUSIPCO 2025), accepted paper, Isola delle Femmine, Italy, Sep. 2025.

You can find the paper here: 10.48550/arXiv.2506.03917.

Usage

Installation

The code runs in a Conda virtual environment, that can be created from the provided yml file:

conda env create -f environment.yml

Running the code

The experiments using the PINN and PIBI models can be run from the scripts pibi_experiments.py and pinn_experiments.py. These scripts can be called from the command line, providing a seed for the random number generator (default: 42).

The PIDL experiments rely on code available at [1]

External references

[1] The code that implements the PIDL method is available at: https://github.com/steDamiano/PIDL-sound-field-reconstruction

[2] The original PIBI-Net code, from which this work was inspired, is available at: https://github.com/MonikaNagy-Huber/PIBI-Net

Acknowledgements

This project has received funding from KU Leuven internal funds C3/23/056 and from FWO Research Project G0A0424N. The resources and services used in this work were provided by the VSC (Flemish Supercomputer Center), funded by the Research Foundation - Flanders (FWO) and the Flemish Government.

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