Andreas Rauh

Uncertainty-Aware Model Learning for Fault Diagnosis

This paper presents two novel algorithms (NDDGD-S and NDDGD-C) that learn Grangercausal propositional logic models from uncertain time-series data by jointly exploiting lower-bound and upper-bound observations of the operating range.