A Review of Classification Algorithms for EEG-based Brain-Computer Interfaces: A 10-year Update F Lotte, L Bougrain, A Cichocki, M Clerc, M Congedo, A Rakotomamonjy, ... Journal of Neural Engineering, 2018 | 1923 | 2018 |
Riemannian approaches in Brain-Computer Interfaces: a review F Yger, M Berar, F Lotte IEEE Transactions on Neural System and Rehabilitation Engineering, 2017 | 376 | 2017 |
Recognizing Art Style Automatically in painting with deep learning A Lecoutre, B Negrevergne, F Yger ACML, 2017 | 161 | 2017 |
A vascular endothelial growth factor-dependent sprouting angiogenesis assay based on an in vitro human blood vessel model for the study of anti-angiogenic drugs J Pauty, R Usuba, IG Cheng, L Hespel, H Takahashi, K Kato, ... EBioMedicine 27, 225-236, 2018 | 119 | 2018 |
Theoretical evidence for adversarial robustness through randomization R Pinot, L Meunier, A Araujo, H Kashima, F Yger, C Gouy-Pailler, J Atif Advances in Neural Information Processing Systems, 2019 | 100 | 2019 |
Geometry-aware principal component analysis for symmetric positive definite matrices I Horev, F Yger, M Sugiyama Machine Learning, 1-30, 2016 | 74 | 2016 |
Geometry-aware principal component analysis for symmetric positive definite matrices I Horev, F Yger, M Sugiyama ACML, 2015 | 74 | 2015 |
Averaging covariance matrices for EEG signal classification based on the CSP: an empirical study F Yger, F Lotte, M Sugiyama 2015 23rd European signal processing conference (EUSIPCO), 2721-2725, 2015 | 61 | 2015 |
sw-SVM: sensor weighting support vector machines for EEG-based brain–computer interfaces N Jrad, M Congedo, R Phlypo, S Rousseau, R Flamary, F Yger, ... Journal of neural engineering 8 (5), 056004, 2011 | 55 | 2011 |
Adaptive canonical correlation analysis based on matrix manifolds F Yger, M Berar, G Gasso, A Rakotomamonjy ICML 2012, 2012 | 52 | 2012 |
Wavelet kernel learning F Yger, A Rakotomamonjy Pattern Recognition 44 (10-11), 2614-2629, 2011 | 45 | 2011 |
Towards adaptive classification using Riemannian geometry approaches in brain-computer interfaces S Kumar, F Yger, F Lotte 2019 7th International Winter Conference on Brain-Computer Interface (BCI), 1-6, 2019 | 43 | 2019 |
A review of kernels on covariance matrices for BCI applications F Yger 2013 IEEE international workshop on machine learning for signal processing …, 2013 | 37 | 2013 |
Supervised logeuclidean metric learning for symmetric positive definite matrices F Yger, M Sugiyama arXiv preprint arXiv:1502.03505, 2015 | 29 | 2015 |
Explainability for regression CNN in fetal head circumference estimation from ultrasound images J Zhang, C Petitjean, F Yger, S Ainouz Workshop on Interpretability of Machine Intelligence in Medical Image …, 2020 | 21 | 2020 |
A unified view on differential privacy and robustness to adversarial examples R Pinot, F Yger, C Gouy-Pailler, J Atif Workshop on Machine Learning for CyberSecurity (MLCS@ECML-PKDD), 2019 | 20 | 2019 |
Uplift modeling from separate labels I Yamane, F Yger, J Atif, M Sugiyama Advances in Neural Information Processing Systems, 2018 | 20 | 2018 |
Using Posters to Recommend Anime and Mangas in a Cold-Start Scenario JJ Vie, F Yger, R Lahfa, B Clement, K Cocchi, T Chalumeau, H Kashima MANPU, 2017 | 20 | 2017 |
Importance-weighted covariance estimation for robust common spatial pattern A Balzi, F Yger, M Sugiyama Pattern Recognition Letters 68, 139-145, 2015 | 20 | 2015 |
Graph-based Clustering under Differential Privacy R Pinot, A Morvan, F Yger, C Gouy-Pailler, J Atif Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial …, 2018 | 19 | 2018 |