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Gaussian process regression was designed for problems with strictly numeric predictor variables. However, GPR can be used with categorical predictor variables by using one-hot encoding.
For functional regression models with functional responses, we propose a nonparametric random-effects model using Gaussian process priors. The proposed model captures the heterogeneity nonlinearly and ...
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