Explore projects

This code base is intended to serve as a starting point for interested researchers or practitioners to extend or apply the uncertainty propagation portion of the author's Master's thesis " GUM-compliant neural-network robustness verification".

This package accompanies my Master's thesis on GUM-compliant neural network robustness verification and provides an implementation using PySCIPOpt.

This codebase provides convenient access to the annotated data set of one electromechanical cylinder at ZeMA testbed.

Demo for PyThia Uncertainty Quantification Toolbox

A simple extension to deep ensembles for an improved uncertainty quantification