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20202023
most citedRandom 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

36 citations · 151 across the 8 of their papers we have counts for

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stat.ME2022★ 25 cited

On the optimization of hyperparameters in Gaussian process regression with the help of low-order high-dimensional model representation

Sergei Manzhos, Manabu Ihara

When the data are sparse, optimization of hyperparameters of the kernel in Gaussian process regression by the commonly used maximum likelihood estimation (MLE) criterion often lead…