Open World Learning Graph Convolution for Latency Estimation in Routing Networks-Reference-Cited by-同舟云学术

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Open World Learning Graph Convolution for Latency Estimation in Routing Networks

Published:2022-07-18 Issue: Volume: Page:
ISSN:
Container-title:2022 International Joint Conference on Neural Networks (IJCNN)
language:
Short-container-title:

Author:

Jin Yifei¹,Daoutis Marios²,Girdzijauskas Sarunas³,Gionis Aristides⁴

Affiliation:

1. KTH Royal Institute of Technology & Ericsson AB,Division of Theoretical and Computer Science & Ericsson Research,Stockholm,Sweden

2. Ericsson AB, Ericsson Research,Stockholm,Sweden

3. KTH Royal Institute of Technology,Division of Software and Computer Systems,Stockholm,Sweden

4. KTH Royal Institute of Technology,Division of Theoretical and Computer Science,Stockholm,Sweden

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9891857/9889787/09892952.pdf?arnumber=9892952

Reference28 articles.

1. Training graph neural networks with 1000 layers;li;ArXiv Preprint,2021

2. Efficient Cipher-Only Attack of a Stream Cipher in RDHEI Based on Pixel Smoothness Estimation

3. Spagan: Shortest path graph attention network;yang;ArXiv Preprint,2021

4. Graph attention networks;veli?kovi?;ArXiv Preprint,2017

5. From local structures to size generalization in graph neural networks;yehudai;ICML,2021

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