Yann Cabanes

According to our database, Yann Cabanes authored at least 9 papers between 2019 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Radar-Based Drone Detection Using Complex-Valued Convolutional Neural Network.

Ankita Dey, Yann Cabanes, Sreeraman Rajan, Bhashyam Balaji, Anthony Damini, Rajkumar Chanchlani

Proceedings of the IEEE Sensors Applications Symposium, 2023

2022

Multidimensional Complex Stationary Centered Gaussian Autoregressive Time Series Machine Learning in Poincaré and Siegel Disks: Application for Audio and Radar Clutter Classification. (Apprentissage dans les disques de Poincaré et de Siegel de séries temporelles multidimensionnelles complexes suivant un modèle autorégressif gaussien stationnaire centré : application à la classification de données audio et de fouillis radar).

Yann Cabanes

PhD thesis, 2022

2021

ICLR 2021 Challenge for Computational Geometry & Topology: Design and Results.

Nina Miolane, Matteo Caorsi, Umberto Lupo, Marius Guerard, Nicolas Guigui, Johan Mathe, Yann Cabanes, Wojciech Reise, Thomas Davies, António Leitão, Somesh Mohapatra, Saiteja Utpala, Shailja Shailja, Gabriele Corso, Guoxi Liu, Federico Iuricich, Andrei Manolache, Mihaela Nistor, Matei Bejan, Armand Mihai Nicolicioiu, Bogdan-Alexandru Luchian, Mihai-Sorin Stupariu, Florent Michel, Khanh Dao Duc, Bilal Abdulrahman, Maxim Beketov, Elodie Maignant, Zhiyuan Liu, Marek Cerný, Martin Bauw, Santiago Velasco-Forero, Jesús Angulo, Yanan Long

CoRR, 2021

${{\, \mathrm{SU}\, }}(1, 1)$ Equivariant Neural Networks and Application to Robust Toeplitz Hermitian Positive Definite Matrix Classification.

Pierre-Yves Lagrave, Yann Cabanes, Frédéric Barbaresco

Proceedings of the Geometric Science of Information - 5th International Conference, 2021

Classification in the Siegel Space for Vectorial Autoregressive Data.

Yann Cabanes, Frank Nielsen

Proceedings of the Geometric Science of Information - 5th International Conference, 2021

2020

The Basic Geometric Structures of Electromagnetic Digital Information: Statistical characterization of the digital measurement of spatio-Doppler and polarimetric fluctuations of the radar electromagnetic wave.

Frédéric Barbaresco, Yann Cabanes

CoRR, 2020

Geomstats: A Python Package for Riemannian Geometry in Machine Learning.

Nina Miolane, Alice Le Brigant, Johan Mathe, Benjamin Hou, Nicolas Guigui, Yann Thanwerdas, Stefan Heyder, Olivier Peltre, Niklas Koep, Hadi Zaatiti, Hatem Hajri, Yann Cabanes, Thomas Gerald, Paul Chauchat, Christian Shewmake, Bernhard Kainz, Claire Donnat, Susan P. Holmes, Xavier Pennec

CoRR, 2020

Introduction to Geometric Learning in Python with Geomstats.

Nina Miolane, Nicolas Guigui, Hadi Zaatiti, Christian Shewmake, Hatem Hajri, Daniel Brooks, Alice Le Brigant, Johan Mathe, Benjamin Hou, Yann Thanwerdas, Stefan Heyder, Olivier Peltre, Niklas Koep, Yann Cabanes, Thomas Gerald, Paul Chauchat, Bernhard Kainz, Claire Donnat, Susan P. Holmes, Xavier Pennec

Proceedings of the 19th Python in Science Conference, 2020

2019

Toeplitz Hermitian Positive Definite Matrix Machine Learning Based on Fisher Metric.

Yann Cabanes, Frédéric Barbaresco, Marc Arnaudon, Jérémie Bigot

Proceedings of the Geometric Science of Information - 4th International Conference, 2019