Invariance priors for Bayesian feed-forward neural networks. - Udo von Toussaint; Silvio Gori; Volker Dose (Neural Networks, 2006)

General Hyperplane Prior Distributions Based on Geometric Invariances for Bayesian Multivariate Linear Regression. - Udo von Toussaint (Entropy, 2015)

Sequential Batch Design for Gaussian Processes Employing Marginalization †. - Roland Preuss; Udo von Toussaint (Entropy, 2017)

Global Optimization Employing Gaussian Process-Based Bayesian Surrogates. - Roland Preuss; Udo von Toussaint (Entropy, 2018)

Bayesian Determination of Parameters for Plasma-Wall Interactions. - Roland Preuss; Rodrigo Arredondo; Udo von Toussaint (Entropy, 2019)

FaVAD: A software workflow for characterization and visualizing of defects in crystalline structures. - Udo von Toussaint; F. Javier Domínguez-Gutiérrez; Michele Compostella; Markus Rampp (Comput. Phys. Commun., 2021)

redmod-team/SympGPR v1.0. - Katharina Rath; Christopher G. Albert; Bernd Bischl; Udo von Toussaint (Zenodo, 2021)

A Bayesian Approach to the Estimation of Parameters and Their Interdependencies in Environmental Modeling. - Christopher G. Albert; Ulrich Callies; Udo von Toussaint (Entropy, 2022)

Epistemic and Aleatoric Uncertainty Quantification and Surrogate Modelling in High-Performance Multiscale Plasma Physics Simulations. - Yehor Yudin; David Coster; Udo von Toussaint; Frank Jenko (ICCS (4), 2023)

Outlier-Robust Surrogate Modeling of Ion-Solid Interaction Simulations. - Roland Preuss; Udo von Toussaint (Entropy, 2023)