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Active Learning with Gaussian Process Regression and Physical Models for Robust SNR Estimation

Research output: Contribution to conference › Paper › peer-review

Standard Standard

Active Learning with Gaussian Process Regression and Physical Models for Robust SNR Estimation. / Ye, Xiaoyan; Mansour, Mariane ; Faruk, Md Saifuddin et al.
2025.

Research output: Contribution to conference › Paper › peer-review

HarvardHarvard

Ye, X, Mansour, M, Faruk, MS, Laperle, C, Reimer, M, O'Sullivan, M & Savory, SJ 2025, 'Active Learning with Gaussian Process Regression and Physical Models for Robust SNR Estimation'.

APA

Ye, X., Mansour, M., Faruk, M. S., Laperle, C., Reimer, M., O'Sullivan, M., & Savory, S. J. (2025). Active Learning with Gaussian Process Regression and Physical Models for Robust SNR Estimation.

CBE

Ye X, Mansour M, Faruk MS, Laperle C, Reimer M, O'Sullivan M, Savory SJ. 2025. Active Learning with Gaussian Process Regression and Physical Models for Robust SNR Estimation.

MLA

Ye, Xiaoyan et al. Active Learning with Gaussian Process Regression and Physical Models for Robust SNR Estimation. Paper, 2025.

VancouverVancouver

Ye X, Mansour M, Faruk MS, Laperle C, Reimer M, O'Sullivan M et al.. Active Learning with Gaussian Process Regression and Physical Models for Robust SNR Estimation. 2025.

Author

Ye, Xiaoyan ; Mansour, Mariane ; Faruk, Md Saifuddin et al. / Active Learning with Gaussian Process Regression and Physical Models for Robust SNR Estimation.

RIS

TY - CONF

T1 - Active Learning with Gaussian Process Regression and Physical Models for Robust SNR Estimation

AU - Ye, Xiaoyan

AU - Mansour, Mariane

AU - Faruk, Md Saifuddin

AU - Laperle, Charles

AU - Reimer, Michael

AU - O'Sullivan, Maurice

AU - Savory, Seb J.

PY - 2025

Y1 - 2025

N2 - We demonstrate improved performance using active learning for both GPRand hybrid models to predict SNR using experimental data from a 15-channel WDMsystem over 1000km. Physical model interpreted GPR agrees with interpretingmeasured data

AB - We demonstrate improved performance using active learning for both GPRand hybrid models to predict SNR using experimental data from a 15-channel WDMsystem over 1000km. Physical model interpreted GPR agrees with interpretingmeasured data

M3 - Paper

ER -