Modeling Electrically Long Interconnects Using Physics-Informed Delayed Gaussian Processes-Reference-Cited by-同舟云学术

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Modeling Electrically Long Interconnects Using Physics-Informed Delayed Gaussian Processes

Published:2023-12 Issue:6 Volume:65 Page:1715-1723
ISSN:0018-9375
Container-title:IEEE Transactions on Electromagnetic Compatibility
language:
Short-container-title:IEEE Trans. Electromagn. Compat.

Author:

Garbuglia Federico¹^ORCID,Reuschel Torsten²^ORCID,Schuster Christian³^ORCID,Deschrijver Dirk¹^ORCID,Dhaene Tom¹^ORCID,Spina Domenico¹^ORCID

Affiliation:

1. Department of Information Technology, Ghent University-imec, Ghent, Belgium

2. Department of Physics, University of New Brunswick (UNB), Fredericton, NB, Canada

3. Institut für Theoretische Elekrotechnik, Hamburg University of Technology (TUHH), Hamburg, Germany

Funder

Vlaamse regering

AI Research Programme

Fonds Wetenschappelijk Onderzoek

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Condensed Matter Physics,Atomic and Molecular Physics, and Optics

Link

http://xplorestaging.ieee.org/ielx7/15/10359425/10268117.pdf?arnumber=10268117

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Conservative Gaussian Process Models for Uncertainty Quantification and Bayesian Optimization in Signal Integrity Applications;IEEE Transactions on Components, Packaging and Manufacturing Technology;2024-07

2. Fast Prediction Method for Scattering Parameters of Rigid-Flex PCBs Based on ANN;Sensors;2024-03-30

3. Deep Neural Network-Based Surrogate-Assisted Inverse Optimization for High-Speed Interconnects;IEEE Transactions on Electromagnetic Compatibility;2024

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