| Deep geometric knowledge distillation with graphs C Lassance, M Bontonou, GB Hacene, V Gripon, J Tang, A Ortega ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 41 | 2020 |
| Introducing graph smoothness loss for training deep learning architectures M Bontonou, C Lassance, GB Hacene, V Gripon, J Tang, A Ortega 2019 IEEE Data Science Workshop (DSW), 160-164, 2019 | 14 | 2019 |
| Few-shot decoding of brain activation maps M Bontonou, G Lioi, N Farrugia, V Gripon 2021 29th European Signal Processing Conference (EUSIPCO), 1326-1330, 2021 | 7 | 2021 |
| Ranking deep learning generalization using label variation in latent geometry graphs C Lassance, L Béthune, M Bontonou, M Hamidouche, V Gripon arXiv preprint arXiv:2011.12737, 2020 | 7 | 2020 |
| Few-shot learning for decoding brain signals M Bontonou, N Farrugia, V Gripon arXiv preprint arXiv:2010.12500, 53, 2020 | 7 | 2020 |
| Predicting the accuracy of a few-shot classifier M Bontonou, L Béthune, V Gripon arXiv preprint arXiv:2007.04238, 2020 | 5 | 2020 |
| Predicting the Generalization Ability of a Few-Shot Classifier M Bontonou, L Béthune, V Gripon Information 12 (1), 29, 2021 | 3 | 2021 |
| Comparing linear structure-based and data-driven latent spatial representations for sequence prediction M Bontonou, C Lassance, V Gripon, N Farrugia Wavelets and Sparsity XVIII 11138, 306-314, 2019 | 3 | 2019 |
| A unified deep learning formalism for processing graph signals M Bontonou, C Lassance, JC Vialatte, V Gripon arXiv preprint arXiv:1905.00496, 2019 | 3 | 2019 |
| Studying Limits of Explainability by Integrated Gradients for Gene Expression Models M Bontonou, A Haget, M Boulougouri, JM Arbona, B Audit, P Borgnat arXiv preprint arXiv:2303.11336, 2023 | 1 | 2023 |
| Graph-LDA: Graph Structure Priors to Improve the Accuracy in Few-Shot Classification M Bontonou, N Farrugia, V Gripon arXiv preprint arXiv:2108.10427, 2021 | 1 | 2021 |
| Expliquer la classification d'expression de gènes par la méthode des gradients intégrés M Bontonou, JM Arbona, B Audit, P Borgnat GRETSI, 29e Colloque sur le traitement du signal et des images, 1233-1236, 2023 | | 2023 |
| Leveraging data structure to learn from few examples: applications to computer vision and neuroimaging M Bontonou Ecole nationale supérieure Mines-Télécom Atlantique, 2021 | | 2021 |
| Similarity between Base and Novel Classes: a Predictor of the Performance in Few-Shot Classification of Brain Activation Maps? M Bontonou, N Farrugia, V Gripon 2021 55th Asilomar Conference on Signals, Systems, and Computers, 1288-1291, 2021 | | 2021 |
| Graphs as Tools to Improve Deep Learning Methods C Lassance, M Bontonou, M Hamidouche, B Pasdeloup, L Drumetz, ... arXiv preprint arXiv:2110.03999, 2021 | | 2021 |
| Un modèle unifié pour la classification de signaux sur graphe avec de l'apprentissage profond M Bontonou, C Lassance, JC Vialatte, V Gripon GRETSI, 2020 | | 2020 |
| PROCESSING GRAPH SIGNALS: A UNIFIED DEEP LEARNING FORMALISM M Bontonou, C Lassance, JC Vialatte, V Gripon | | |
Vincent GriponIMT Atlantique and Lab-STICCVerified email at imt-atlantique.fr
