| Lipschitz regularity of deep neural networks: analysis and efficient estimation A Virmaux, K Scaman Advances in Neural Information Processing Systems 31, 2018 | 566 | 2018 |
| Coloring graph neural networks for node disambiguation G Dasoulas, LD Santos, K Scaman, A Virmaux arXiv preprint arXiv:1912.06058, 2019 | 84 | 2019 |
| Lipschitz normalization for self-attention layers with application to graph neural networks G Dasoulas, K Scaman, A Virmaux International Conference on Machine Learning, 2456-2466, 2021 | 35 | 2021 |
| Ego-based entropy measures for structural representations on graphs G Dasoulas, G Nikolentzos, K Seaman, A Virmaux, M Vazirgiannis ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 8* | 2021 |
| Improving hierarchical adversarial robustness of deep neural networks A Ma, A Virmaux, K Scaman, J Lu arXiv preprint arXiv:2102.09012, 2021 | 6 | 2021 |
| Unlocking the potential of transformers in time series forecasting with sharpness-aware minimization and channel-wise attention R Ilbert, A Odonnat, V Feofanov, A Virmaux, G Paolo, T Palpanas, I Redko arXiv preprint arXiv:2402.10198, 2024 | 5 | 2024 |
| Random matrix analysis to balance between supervised and unsupervised learning under the low density separation assumption V Feofanov, M Tiomoko, A Virmaux International Conference on Machine Learning, 10008-10033, 2023 | 4 | 2023 |
| Deciphering lasso-based classification through a large dimensional analysis of the iterative soft-thresholding algorithm M Tiomoko, E Schnoor, MEA Seddik, I Colin, A Virmaux International Conference on Machine Learning, 21449-21477, 2022 | 3 | 2022 |
| Density Estimation For Conversative Q-Learning P Daoudi, L Dos Santos, M Barlier, A Virmaux | 3 | 2022 |
| Non-commutative Frobenius characteristic of generalized parking functions: Application to enumeration JB Priez, A Virmaux Discrete Mathematics & Theoretical Computer Science, 2015 | 2 | 2015 |
| On the partial categorification of some Hopf algebras using the representation theory of towers of J-trivial monoids and semilattices A Virmaux FPSAC'14, 2014 | 2* | 2014 |
| Meta-learning of black-box solvers using deep reinforcement learning S Chaybouti, L Dos Santos, C Malherbe, A Virmaux NeurIPS 2022, MetaLearn Workshop, 2022 | 1 | 2022 |
| Node disambiguation G Dasoulas, L Dos Santos, K Scaman, A Virmaux US Patent App. 17/702,064, 2022 | 1 | 2022 |
| SAMformer: Unlocking the Potential of Transformers in Time Series Forecasting with Sharpness-Aware Minimization and Channel-Wise Attention R Ilbert, A Odonnat, V Feofanov, A Virmaux, G Paolo, T Palpanas, I Redko Forty-first International Conference on Machine Learning, 0 | 1 | |
| Normalization scheme for self-attention neural networks A Virmaux, G Dasoulas, K Scaman US Patent App. 18/365,047, 2023 | | 2023 |
| Devices and methods for controlling base stations of a communication network E Malherbe, A Virmaux, S Chouvardas, M Draief US Patent 11,412,447, 2022 | | 2022 |
| Knothe-Rosenblatt transport for Unsupervised Domain Adaptation A Virmaux, I Saffar, J Zhang, B Kégl arXiv preprint arXiv:2110.02716, 2021 | | 2021 |
| Combinatorial representation theory of tower monoids: Application to categorification and to parking functions A Virmaux HAL 2016, 2016 | | 2016 |
| EMTL: A Generative Domain Adaptation Approach J Zhang, I Saffar, A Virmaux, B Kégl | | |
Kevin ScamanResearch scientist, INRIAVerified email at inria.fr
