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A deep learning auto-regressive method is trained to learn the acoustic propagation in presence of obstacles. The method is flexible to account for both far-fields prediction (non-reflecting cases) as well as duct acoustics (non-reflecting BCs).

This repository contains "experimental modular TFA" (aka xtfa), a python-implementation of the algorithms and data structures that I have developed during my thesis. For more information on the theoretical grounds, please consult my manuscript.

Projet public mettant à disposition l’exécutable d'installation

A project investigating the invertability of random matrices over a finite field.

Explores ways to branch an RNG to measure things about a random process without changing the state of the RNG when doing measures or not.

https://gitlab-pages.isae-supaero.fr/dragoon/komodo-benchmark-results/

awesome_ros2_tutorials is a gitlab project who containt the docs, and the packages for taking in hand ros2 in the isae autonomous platform.

Copy of the original CREME project scripts. This copy is used to learn the functioning of the original simulations and modify it.

Library for performing acoustic beamforming from signal obtained with an array of microphones.

A CLI application to plot data with Matplotlib.

forked from https://github.com/amtoine/dotfiles

Nanospace Docker Images (Front-End/Back-End)