David Ginsbourger

Continuous logistic Gaussian random measure fields for spatial distributional modelling

Abstract We study Spatial Logistic Gaussian Process (SLGP) models for non-parametric estimation of probability density fields using scattered samples of heterogeneous sizes. SLGPs are examined from the perspective of random measures and their densities, investigating the relation...

Gaussian Process Modeling with Genotype $$\times $$ Environment Kernels for Wheat Performance Prediction

Abstract Optimizing wheat variety selection for high performance in different environmental conditions is critical for reliable food production and stable incomes for growers. We employ a statistical machine learning framework utilizing Gaussian process (GP) models to capture the...