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Deep reinforcement learning meets graph neural networks: Exploring a routing optimization use case., , , , and . Comput. Commun., (2022)Towards Real-Time Routing Optimization with Deep Reinforcement Learning: Open Challenges., , , , , and . HPSR, page 1-6. IEEE, (2021)Digital Twin Network: Opportunities and Challenges., , , , , , , , , and 6 other author(s). CoRR, (2022)Towards more realistic network models based on Graph Neural Networks., , , , , and . CoNEXT Companion, page 14-16. ACM, (2019)RouteNet: Leveraging Graph Neural Networks for network modeling and optimization in SDN., , , , and . CoRR, (2019)Deep Reinforcement Learning meets Graph Neural Networks: An optical network routing use case., , , , , and . CoRR, (2019)Leveraging Spatial and Temporal Correlations for Network Traffic Compression., , , , , , and . CoRR, (2023)RouteNet: Leveraging Graph Neural Networks for Network Modeling and Optimization in SDN., , , , and . IEEE J. Sel. Areas Commun., 38 (10): 2260-2270 (2020)ENERO: Efficient real-time WAN routing optimization with Deep Reinforcement Learning., , , , , and . Comput. Networks, (2022)Securing the Control-plane Channel and Cache of Pull-based ID/LOC Protocols., , , , , , , and . CoRR, (2018)