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 example, ...

Herlands, William, Edward McFowland III, Andrew Gordon Wilson, and Daniel B. Neill. "Gaussian Process Subset Scanning for Anomalous Pattern Detection in Non-iid Data." Proceedings of Machine Learning ...

Poisson Process – memoryless properties, alternative definitions, combining and splitting. Finite State Markov chains – first passage time analysis, steady-state analysis Gaussian Processes – jointly ...

Understanding Gaussian Process Regression I suspect that one of the reasons why Gaussian process regression is not used as often as other regression techniques is that GPR is very intimidating from a ...

Researchers explored the decision-making process of Gaussian process (GP) models, focusing on loss landscapes and hyperparameter optimization. They emphasized the importance of the Matérn kernel ...