All-Terminal Network Reliability Estimation with Graph Neural Networks-Reference-Cited by-同舟云学术

All-Terminal Network Reliability Estimation with Graph Neural Networks

Published:2022-01-24 Issue: Volume: Page:
ISSN:
Container-title:2022 Annual Reliability and Maintainability Symposium (RAMS)
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Author:

Davila-Frias Alex¹,Yadav Om Prakash²,Salem Saeed³,Jain Rakesh⁴

Affiliation:

1. Escuela Politécnica Nacional

2. North Carolina A&T State University

3. North Dakota State University

4. Malaviya National Institute of Technology

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9893903/9893894/09893982.pdf?arnumber=9893982

Reference9 articles.

1. Deep Neural Networks for All-Terminal Network Reliability Estimation

2. All-terminal network reliability estimation using convolutional neural networks;davila-frias;Proceedings of the Institution of Mechanical Engineers Part O Journal of Risk and Reliability,2020

3. Interaction networks for learning about objects, relations and physics;battaglia;Advances in neural information processing systems Barcelona,2016

4. All-Terminal Network Reliability Estimation with Monte Carlo and Deep Neural Networks;davila-frias;Proceedings of the 2021 IISE Annual Conference,2021

5. Graph Neural Networks in TensorFlow and Keras with Spektral [Application Notes]

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