Modeling S-parameters of Interconnects using Periodic Gaussian Process Kernels-Reference-Cited by-同舟云学术

Modeling S-parameters of Interconnects using Periodic Gaussian Process Kernels

Published:2023-05-07 Issue: Volume: Page:
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Container-title:2023 IEEE 27th Workshop on Signal and Power Integrity (SPI)
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Author:

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

Affiliation:

1. Ghent University-imec,IDLab,Ghent,Belgium

2. University of New Brunswick,Fredericton,NB,Canada

3. Hamburg University of Technology,Hamburg,Germany

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10145490/10145514/10145548.pdf?arnumber=10145548

Reference10 articles.

1. Bayesian Active Learning for Radiation Pattern Sampling Over Cylindrical Surfaces

2. Gaussian process kernels for pattern discovery and extrapolation;wilson;Proceedings of the 30th International Conference on Machine Learning ser Proceedings of Machine Learning Research,2013

3. Efficient Prediction of Equalization Effort and Channel Performance for PCB-Based Data Links

4. Regression

5. Machine Learning and Uncertainty Quantification for Surrogate Models of Integrated Devices With a Large Number of Parameters

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