| Unveiling the potential of Graph Neural Networks for network modeling and optimization in SDN K Rusek, J Suárez-Varela, A Mestres, P Barlet-Ros, A Cabellos-Aparicio Proceedings of the ACM Symposium on SDN Research (SOSR), 140-151, 2019 | 101 | 2019 |
| RouteNet: Leveraging Graph Neural Networks for network modeling and optimization in SDN K Rusek, J Suárez-Varela, P Almasan, P Barlet-Ros, A Cabellos-Aparicio IEEE Journal on Selected Areas in Communications (JSAC), 2020 | 88 | 2020 |
| Deep Reinforcement Learning meets Graph Neural Networks: exploring a routing optimization use case P Almasan, J Suárez-Varela, A Badia-Sampera, K Rusek, P Barlet-Ros, ... arXiv, arXiv: 1910.07421, 2019 | 61 | 2019 |
| Routing in optical transport networks with deep reinforcement learning J Suárez-Varela, A Mestres, J Yu, L Kuang, H Feng, A Cabellos-Aparicio, ... Journal of Optical Communications and Networking 11, 547-558, 2019 | 37 | 2019 |
| Feature engineering for Deep Reinforcement Learning based routing J Suárez-Varela, A Mestres, J Yu, L Kuang, H Feng, P Barlet-Ros, ... IEEE International Conference on Communications (ICC), 2019 | 30 | 2019 |
| Routing Based on Deep Reinforcement Learning in Optical Transport Networks J Suárez-Varela, A Mestres, J Yu, L Kuang, H Feng, P Barlet-Ros, ... Optical Fiber Communications Conference and Exhibition (OFC), San Diego, USA, 2019 | 29 | 2019 |
| Flow monitoring in Software-Defined Networks: Finding the accuracy/performance tradeoffs J Suárez-Varela, P Barlet-Ros Computer Networks 135, 289-301, 2018 | 28 | 2018 |
| Towards a NetFlow implementation for OpenFlow Software-Defined Networks J Suárez-Varela, P Barlet-Ros 29th International Teletraffic Congress (ITC), 2017 1, 187-195, 2017 | 25 | 2017 |
| Challenging the generalization capabilities of Graph Neural Networks for network modeling J Suárez-Varela, S Carol-Bosch, K Rusek, P Almasan, M Arias, ... Proceedings of ACM SIGCOMM Posters and Demos, 114-115, 2019 | 22 | 2019 |
| Detecting cryptocurrency miners with NetFlow/IPFIX network measurements J Zayuelas i Muñoz, J Suárez-Varela, P Barlet-Ros IEEE International Symposium on Measurements and Networking (M&N), 2019 | 19 | 2019 |
| SBAR: SDN flow-Based monitoring and Application Recognition J Suárez-Varela, P Barlet-Ros Proceedings of the Symposium on SDN Research (SOSR), 2018 | 14 | 2018 |
| Reinventing NetFlow for OpenFlow Software-Defined Networks (technical report) J Suárez-Varela, P Barlet-Ros arXiv preprint arXiv:1702.06803, 2017 | 13 | 2017 |
| Towards more realistic network models based on Graph Neural Networks A Badia-Sampera, J Suárez-Varela, P Almasan, K Rusek, P Barlet-Ros, ... Proceedings of ACM CoNEXT student workshop, 14-16, 2019 | 9 | 2019 |
| Is Machine Learning Ready for Traffic Engineering Optimization? G Bernárdez, J Suárez-Varela, A López, B Wu, S Xiao, X Cheng, ... IEEE International Conference on Network Protocols (ICNP), 2021 | 8 | 2021 |
| IGNNITION: Bridging the Gap between Graph Neural Networks and Networking Systems D Pujol-Perich, J Suárez-Varela, M Ferriol, S Xiao, B Wu, ... IEEE Network 35 (6), 171-177, 2021 | 7 | 2021 |
| Applying Graph-based Deep Learning To Realistic Network Scenarios M Ferriol-Galmés, J Suárez-Varela, P Barlet-Ros, A Cabellos-Aparicio arXiv preprint arXiv:2010.06686, 2020 | 6 | 2020 |
| Network Digital Twin: Context, Enabling Technologies and Opportunities P Almasan, M Ferriol-Galmés, J Paillisse, J Suárez-Varela, D Perino, ... arXiv preprint arXiv:2205.14206, 2022 | 5* | 2022 |
| The Graph Neural Networking Challenge: A Worldwide Competition for Education in AI/ML for Networks J Suárez-Varela, M Ferriol-Galmés, A López, P Almasan, G Bernárdez, ... ACM SIGCOMM Computer Communication Review 51 (3), 2021 | 5 | 2021 |
| Scaling Graph-based Deep Learning models to larger networks M Ferriol-Galmés, J Suárez-Varela, K Rusek, P Barlet-Ros, ... arXiv preprint arXiv:2110.01261, 2021 | 4 | 2021 |
| Towards Real-Time Routing Optimization with Deep Reinforcement Learning: Open Challenges P Almasan, J Suárez-Varela, B Wu, S Xiao, P Barlet-Ros, ... IEEE HPSR SARNET, 2021 | 3 | 2021 |
