| Lipschitz regularity of deep neural networks: analysis and efficient estimation A Virmaux, K Scaman Advances in Neural Information Processing Systems 31, 2018 | 250 | 2018 |
| Optimal algorithms for smooth and strongly convex distributed optimization in networks K Scaman, F Bach, S Bubeck, YT Lee, L Massoulié Proceedings of the 34th International Conference on Machine Learning-Volume …, 2017 | 248 | 2017 |
| Optimal algorithms for non-smooth distributed optimization in networks K Scaman, F Bach, S Bubeck, L Massoulié, YT Lee Advances in Neural Information Processing Systems 31, 2018 | 139 | 2018 |
| Optimal convergence rates for convex distributed optimization in networks K Scaman, F Bach, S Bubeck, Y Lee, L Massoulié Journal of Machine Learning Research 20, 1-31, 2019 | 47 | 2019 |
| Multivariate Hawkes processes for large-scale inference R Lemonnier, K Scaman, A Kalogeratos Proceedings of the AAAI conference on artificial intelligence 31 (1), 2017 | 32 | 2017 |
| Coloring graph neural networks for node disambiguation G Dasoulas, LD Santos, K Scaman, A Virmaux arXiv preprint arXiv:1912.06058, 2019 | 30 | 2019 |
| Suppressing epidemics in networks using priority planning K Scaman, A Kalogeratos, N Vayatis IEEE Transactions on Network Science and Engineering 3 (4), 271-285, 2016 | 29* | 2016 |
| Tight bounds for influence in diffusion networks and application to bond percolation and epidemiology R Lemonnier, K Scaman, N Vayatis Advances in Neural Information Processing Systems 27, 2014 | 21 | 2014 |
| A greedy approach for dynamic control of diffusion processes in networks K Scaman, A Kalogeratos, N Vayatis 2015 IEEE 27th International Conference on Tools with Artificial …, 2015 | 14 | 2015 |
| Robustness analysis of non-convex stochastic gradient descent using biased expectations K Scaman, C Malherbe Advances in Neural Information Processing Systems 33, 16377-16387, 2020 | 13 | 2020 |
| Anytime influence bounds and the explosive behavior of continuous-time diffusion networks K Scaman, R Lemonnier, N Vayatis Advances in Neural Information Processing Systems 28, 2015 | 12 | 2015 |
| Theoretical limits of pipeline parallel optimization and application to distributed deep learning I Colin, L Dos Santos, K Scaman Advances in Neural Information Processing Systems 32, 2019 | 6 | 2019 |
| Dynamic treatment allocation for epidemic control in arbitrary networks K Scaman, A Kalogeratos, N Vayatis Diffusion Networks and Cascade Analytics workshop, 2014 | 6 | 2014 |
| Ego-based entropy measures for structural representations on graphs G Dasoulas, G Nikolentzos, K Scaman, A Virmaux, M Vazirgiannis ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 5* | 2021 |
| Spectral bounds in random graphs applied to spreading phenomena and percolation R Lemonnier, K Scaman, N Vayatis Advances in Applied Probability 50 (2), 480-503, 2018 | 4 | 2018 |
| Information diffusion and rumor spreading A Kalogeratos, K Scaman, L Corinzia, N Vayatis Cooperative and Graph Signal Processing, 651-678, 2018 | 4 | 2018 |
| A spectral method for activity shaping in continuous-time information cascades K Scaman, A Kalogeratos, L Corinzia, N Vayatis arXiv preprint arXiv:1709.05231, 2017 | 4 | 2017 |
| Learning to suppress SIS epidemics in networks A Kalogeratos, K Scaman, N Vayatis Networks in the Social and Information Sciences workshop, 2015 | 4 | 2015 |
| 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 | 3 | 2021 |
| KONG: Kernels for ordered-neighborhood graphs M Draief, K Kutzkov, K Scaman, M Vojnovic Advances in Neural Information Processing Systems 31, 2018 | 3 | 2018 |
Nicolas VayatisProfesseur des universités, ENS Paris-SaclayVerified email at ens-paris-saclay.fr
