Applying Graph-based Deep Learning To Realistic Network Scenarios

13 October 2020

Papers citing "Applying Graph-based Deep Learning To Realistic Network Scenarios"

6 / 6 papers shown

Title
DeepRMSA: A Deep Reinforcement Learning Framework for Routing, Modulation and Spectrum Assignment in Elastic Optical Networks Xiaoliang Chen Baojia Li R. Proietti Hongbo Lu Zuqing Zhu S. Yoo 35 166 0 06 May 2019
Graph Neural Networks: A Review of Methods and Applications Jie Zhou Ganqu Cui Shengding Hu Zhengyan Zhang Cheng Yang Zhiyuan Liu Lifeng Wang Changcheng Li Maosong Sun AI4CE GNN 1.1K 5,517 0 20 Dec 2018
Understanding the Modeling of Computer Network Delays using Neural Networks Albert Mestres Eduard Alarcón Yusheng Ji A. Cabellos-Aparicio 38 54 0 23 Jul 2018
Experience-driven Networking: A Deep Reinforcement Learning based Approach Zhiyuan Xu Jian Tang Jingsong Meng Weiyi Zhang Yanzhi Wang C. Liu Dejun Yang OffRL 57 362 0 17 Jan 2018
Neural Message Passing for Quantum Chemistry Justin Gilmer S. Schoenholz Patrick F. Riley Oriol Vinyals George E. Dahl 593 7,455 0 04 Apr 2017
Interaction Networks for Learning about Objects, Relations and Physics Peter W. Battaglia Razvan Pascanu Matthew Lai Danilo Jimenez Rezende Koray Kavukcuoglu AI4CE OCL PINN GNN 533 1,410 0 01 Dec 2016