Results 201 to 210 of about 14,298 (230)

Non-Modellable Risk Factor (NMRF) Measurement Using Gaussian Process Regression (GPR)

SSRN Electronic Journal, 2018
One innovation defined in the new market risk rules by the Fundamental Review of the Trading Book (FRTB) is the Non-Modellable Risk Factor (NMRF) framework. This new concept introduces a methodology to differentiate between modellable and non-modellable risk factors in the Internal Models Approach (IMA).
openaire   +1 more source

Random Sampling High Dimensional Model Representation Gaussian Process Regression (RS-HDMR-GPR) for Multivariate Function Representation: Application to Molecular Potential Energy Surfaces

The Journal of Physical Chemistry A, 2020
We present an approach combining a representation of a multivariate function using subdimensional functions with machine learning based representation of component functions: Random sampling high dimensional model representation Gaussian process regression (RS-HDMR-GPR).
Mohamed Ali Boussaidi, Owen Ren, Dmitry Voytsekhovsky, Sergei Manzhos   +3 more
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Plate-like structures damage detection based on static response and static strain energy using gaussian process regression (GPR)

Inverse Problems in Science and Engineering, 2017
This study investigates the applicability of an emergent learning algorithm called Gaussian process regression (GPR) algorithm to predict damage in plate-like structures as an inverse problem.
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Application of Gaussian Process Regression (GPR) in estimating under-five mortality levels and trends in Iran 1990 - 2013, study protocol.

Archives of Iranian medicine, 2014
Searching for the latest methods of estimating mortality rates is a major concern for researchers who are working in burden of diseases. Child mortality is an important indicator for assessing population health care services in a country. The National and Sub-national Burden of Diseases, Injuries, and Risk Factors (NASBOD) is conducted in Iran with ...
Parinaz, Mehdipour, Iman, Navidi, Mahboubeh, Parsaeian, Younes, Mohammadi, Maziar, Moradi Lakeh, Ehsan, Rezaei Darzi, Keramat, Nourijelyani, Farshad, Farzadfar   +7 more
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Prediction of Uniaxial Compressive Strength Using Fully Bayesian Gaussian Process Regression (fB-GPR) with Model Class Selection

Rock Mechanics and Rock Engineering, 2022
Tengyuan Zhao, Chao Song, Shifeng Lu, Ling Xu   +3 more
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Implementation Of Monitoring And Prediction Of Humidity, Temperature, and Light using Gaussian Process Regression (GPR) For Orchid Green House In Lembang

2023 IEEE International Conference on Communication, Networks and Satellite (COMNETSAT), 2023
Aditya Fauziah, Hilal H. Nuha
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Prediction of Temperature and Humidity at Telkom University Landmark Tower (TULT) Using Gaussian Process Regression (GPR) and Internet of Things (IoT)

2023 International Conference on Data Science and Its Applications (ICoDSA), 2023
Angga Christian Simatupang, Hilal H. Nuha   +1 more
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Random Sampling High Dimensional Model Representation Gaussian Process Regression (RS-HDMR-GPR) for representing multidimensional functions with machine-learned lower-dimensional terms allowing insight with a general method

Computer Physics Communications, 2022
Manabu Ihara, Sergei Manzhos
exaly  

Details on Gaussian Process Regression (GPR) and Semi-GPR Modeling

2019
Shekaramiz, Mohammad, T.K. Moon, Gunther, Jake   +2 more
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Benchmarking of Gaussian Process Regression with Multiple Random Fields for Spatial Variability Estimation

ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 2022
Ikumasa Yoshida
exaly