| 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 32, 2019 | 42 | 2019 |
| Advocating for Multiple Defense Strategies against Adversarial Examples A Araujo, L Meunier, R Pinot, B Negrevergne Workshop on Machine Learning for CyberSecurity (MLCS@ECML-PKDD), 2020 | 25* | 2020 |
| Training compact deep learning models for video classification using circulant matrices A Araujo, B Negrevergne, Y Chevaleyre, J Atif The European Conference on Computer Vision (ECCV) Workshops, 2018 | 13 | 2018 |
| On Lipschitz Regularization of Convolutional Layers using Toeplitz Matrix Theory A Araujo, B Negrevergne, Y Chevaleyre, J Atif Proceedings of the AAAI Conference on Artificial Intelligence 35, 2020 | 6 | 2020 |
| Understanding and Training Deep Diagonal Circulant Neural Networks A Araujo, B Negrevergne, Y Chevaleyre, J Atif 24th European Conference on Artificial Intelligence - ECAI 2020, 2019 | 2* | 2019 |
| A Dynamical System Perspective for Lipschitz Neural Networks L Meunier, B Delattre, A Araujo, A Allauzen International Conference on Machine Learning (ICML), 2021 | | 2021 |
| Building Compact and Robust Deep Neural Networks with Toeplitz Matrices A Araujo PhD Thesis, 2021 | | 2021 |
Laurent MeunierFAIR Paris, MILES LAMSADE Université Paris DauphineVerified email at dauphine.eu
