| Geomstats: A python package for riemannian geometry in machine learning N Miolane, N Guigui, A Le Brigant, J Mathe, B Hou, Y Thanwerdas, ... Journal of Machine Learning Research 21 (223), 1-9, 2020 | 111 | 2020 |
| Toeplitz Hermitian positive definite matrix machine learning based on Fisher metric Y Cabanes, F Barbaresco, M Arnaudon, J Bigot Geometric Science of Information: 4th International Conference, GSI 2019 …, 2019 | 19 | 2019 |
| Unsupervised machine learning for pathological radar clutter clustering: The p-mean-shift algorithm Y Cabanes, F Barbaresco, M Arnaudon, J Bigot C&ESAR 2019, 2019 | 17 | 2019 |
| Iclr 2021 challenge for computational geometry & topology: Design and results N Miolane, M Caorsi, U Lupo, M Guerard, N Guigui, J Mathe, Y Cabanes, ... arXiv preprint arXiv:2108.09810, 2021 | 16 | 2021 |
| Introduction to geometric learning in python with geomstats N Miolane, N Guigui, H Zaatiti, C Shewmake, H Hajri, D Brooks, ... SciPy 2020-19th Python in Science Conference, 48-57, 2020 | 13 | 2020 |
| Non-supervised machine learning algorithms for radar clutter high-resolution Doppler segmentation and pathological clutter analysis Y Cabanes, F Barbaresco, M Arnaudon, J Bigot 2019 20th International Radar Symposium (IRS), 1-10, 2019 | 11 | 2019 |
| Multidimensional complex stationary centered Gaussian autoregressive time series machine learning in Poincaré and Siegel disks: application for audio and radar clutter … Y Cabanes Université de Bordeaux, 2022 | 9 | 2022 |
| Equivariant Neural Networks and Application to Robust Toeplitz Hermitian Positive Definite Matrix Classification PY Lagrave, Y Cabanes, F Barbaresco International Conference on Geometric Science of Information, 577-584, 2021 | 9 | 2021 |
| Classification in the Siegel Space for Vectorial Autoregressive Data Y Cabanes, F Nielsen Geometric Science of Information: 5th International Conference, GSI 2021 …, 2021 | 9 | 2021 |
| Non-supervised high resolution Doppler machine learning for pathological radar clutter Y Cabanes, F Barbaresco, M Arnaudon, J Bigot 2019 International Radar Conference (RADAR), 1-6, 2019 | 8 | 2019 |
| Radar-based drone detection using complex-valued convolutional neural network A Dey, Y Cabanes, S Rajan, B Balaji, A Damini, R Chanchlani 2023 IEEE Sensors Applications Symposium (SAS), 1-5, 2023 | 7 | 2023 |
| An equivariant neural network with hyperbolic embedding for robust doppler signal classification PY Lagrave, Y Cabanes, F Barbaresco 2021 21st International Radar Symposium (IRS), 1-9, 2021 | 6 | 2021 |
| Geomstats: A Python Package for Riemannian Geometry in Machine Learning. 2020 N Miolane, A Le Brigant, Y Cabanes arXiv preprint arXiv:2004.04667, 0 | 5 | |
| Apprentissage dans les disques de Poincaré et de Siegel de séries temporelles multidimensionnelles complexes suivant un modèle autorégressif gaussien stationnaire centré … Y Cabanes Bordeaux, 2022 | 1 | 2022 |
| Matrix extension for pathological radar clutter machine learning Y Cabanes, F Barbaresco, M Arnaudon, J Bigot | 1 | 2020 |
| The Basic Geometric Structures of Electromagnetic Digital Information: Statistical characterization of the digital measurement of spatio-Doppler and polarimetric fluctuations … F Barbaresco, Y Cabanes arXiv preprint arXiv:2007.00428, 2020 | | 2020 |
| Learning of Pathological Radar Clutter using Supervised and Un-supervised Classification Meth-ods Y CABANES Résumés Étendus des Thèses de Doctorat de Troisième Année 2020, 2020 | | 2020 |
| APPROCHER LES DEUX INFINIS PAR LES ONDES ELECTROMAGNETIQUES LES STRUCTURES GÉOMÉTRIQUES ÉLÉMENTAIRES DE L'INFORMATION DIGITALE ÉLECTROMAGNÉTIQUE Caractérisation statistique de … F Barbaresco, Y Cabanes JS19, 2019 | | 2019 |
| Quantum nearest mean classifier on the Bloch sphere: an efficient prediction method for binary classification tasks Y Cabanes, C Pere, S Corbeil-Letourneau, F Holweck, S Rajan, B Balaji, ... quantum 2 (1y), 2, 0 | | |
| Radar-based Drone Detection in Poincaré disks Y Cabanes, S Rajan, B Balaji | | |
