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2020 – today
- 2023
[c5]Ankita Dey, Yann Cabanes, Sreeraman Rajan, Bhashyam Balaji, Anthony Damini, Rajkumar Chanchlani:
Radar-Based Drone Detection Using Complex-Valued Convolutional Neural Network. SAS 2023: 1-5- 2022
- [b1]Yann Cabanes:
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). University of Bordeaux, France, 2022 - 2021
- [c4]Pierre-Yves Lagrave
, Yann Cabanes, Frédéric Barbaresco:
${{\, \mathrm{SU}\, }}(1, 1)$ Equivariant Neural Networks and Application to Robust Toeplitz Hermitian Positive Definite Matrix Classification. GSI 2021: 577-584 - [c3]Yann Cabanes, Frank Nielsen:
Classification in the Siegel Space for Vectorial Autoregressive Data. GSI 2021: 693-700 - [i3]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:
ICLR 2021 Challenge for Computational Geometry & Topology: Design and Results. CoRR abs/2108.09810 (2021) - 2020
- [c2]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:
Introduction to Geometric Learning in Python with Geomstats. SciPy 2020: 48-57 - [i2]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:
Geomstats: A Python Package for Riemannian Geometry in Machine Learning. CoRR abs/2004.04667 (2020) - [i1]Frédéric Barbaresco, Yann Cabanes:
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. CoRR abs/2007.00428 (2020)
2010 – 2019
- 2019
- [c1]Yann Cabanes, Frédéric Barbaresco, Marc Arnaudon, Jérémie Bigot:
Toeplitz Hermitian Positive Definite Matrix Machine Learning Based on Fisher Metric. GSI 2019: 261-270
Coauthor Index
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