SCHWANDER Olivier
Fecha de salida : 31/12/2021
2020
BROOKS Daniel : Apprentissage profond et géométrie de l'information pour la classification des séries chronologiques .
Publicaciones 2016-2020
Ellas todas
Artículos de revistas
Documentos de conferencias
2020
E. Moschos, A. Stegner, O. Schwander, P. Gallinari : “Classification of Eddy Sea Surface Temperature Signatures Under Cloud Coverage ”, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 13, pp. 3437-3447, (IEEE) (2020)E. Moschos, O. Schwander, A. Stegner, P. Gallinari : “DEEP-SST-EDDIES: A Deep Learning framework to detect oceanic eddies in Sea Surface Temperature images ”, ICASSP 2020 - 45th International Conference on Acoustics, Speech, and Signal Processing, Barcelona, Spain, pp. 4307-4311 (2020)
2019
D. Brooks, O. Schwander, F. Barbaresco, J.‑Y. Schneider, M. Cord : “Riemannian batch normalization for SPD neural networks ”, Thirty-third Annual Conference on Neural Information Processing Systems., Vancouver, Canada (2019)D. Brooks, O. Schwander, F. Barbaresco, J.‑Y. Schneider, M. Cord : “A Hermitian Positive Definite neural network for micro-Doppler complex covariance processing ”, International Radar Conference, Toulon, France (2019)D. Brooks, O. Schwander, F. Barbaresco, J.‑Y. Schneider, M. Cord : “Second-order networks in PyTorch ”, GSI 2019 - 4th International Conference on Geometric Science of Information, vol. 11712, Lecture Notes in Computer Science, Toulouse, France, pp. 751-758, (Springer) (2019)D. Brooks, O. Schwander, F. Barbaresco, J.‑Y. Schneider, M. Cord : “Complex-valued neural networks for fully-temporal micro-Doppler classification ”, 2019 20th International Radar Symposium (IRS), 2019 20th International Radar Symposium (IRS), Ulm, Germany, (IEEE) (2019)D. Brooks, O. Schwander, F. Barbaresco, J.‑Y. Schneider, M. Cord : “Exploring Complex Time-series Representations for Riemannian Machine Learning of Radar Data ”, ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing, Brighton, United Kingdom, pp. 3672-3676, (IEEE) (2019)T. Véniat, O. Schwander, L. Denoyer : “STOCHASTIC ADAPTIVE NEURAL ARCHITECTURE SEARCH FOR KEYWORD SPOTTING ”, ICASSP 2019 - International Conference on Acoustics, Speech, and Signal Processing, Brighton, United Kingdom (2019)
2018
D. Brooks, O. Schwander, F. Barbaresco, J.‑Y. Schneider, M. Cord : “Temporal Deep Learning for Drone Micro-Doppler Classification ”, IRS 2018 - 19th International Radar Symposium, Bonn, Germany, (IEEE) (2018)A. Lopez‑Rincon, A. Tonda, M. Elati, O. Schwander, B. Piwowarski, P. Gallinari : “Evolutionary optimization of convolutional neural networks for cancer miRNA biomarkers classification ”, Applied Soft Computing, vol. 65, pp. 91-100, (Elsevier) (2018)P. Gallinari, Y. Maday, M. Sangnier, O. Schwander, T. Taddei : “Reduced Basis’ Acquisition by a Learning Process for Rapid On-line Approximation of Solution to PDE’s: Laminar Flow Past a Backstep ”, Archives of Computational Methods in Engineering, vol. 25 (1), pp. 131-141, (Springer Verlag) (2018)
2016
