Mixtures of Gaussian Processes for regression under multiple prior distributions. - Sarem Seitz (CoRR, 2021)

Self-explaining variational posterior distributions for Gaussian Process models. - Sarem Seitz (CoRR, 2021)

Self-Explaining Variational Gaussian Processes for Transparency and Modelling of Prior Knowledge. - Sarem Seitz (KI (Workshops), 2022)

Mixture density networks for the indirect estimation of reference intervals. - Tobias Hepp 001; Jakob Zierk; Manfred Rauh; Markus Metzler; Sarem Seitz (BMC Bioinform., 2022)

A piece-wise constant approximation for non-conjugate Gaussian Process models. - Sarem Seitz (CoRR, 2022)

Gradient-based explanations for Gaussian Process regression and classification models. - Sarem Seitz (CoRR, 2022)