no code implementations • 20 Jan 2024 • Christoph Wehner, Maximilian Kertel, Judith Wewerka
In addition, an Interactive User Interface enables a process expert to give feedback to the root cause graph by adding and removing information to the Knowledge Graph.
no code implementations • 12 Jan 2024 • Maximilian Kertel, Nadja Klein
We present a boosting-based method to learn additive Structural Equation Models (SEMs) from observational data, with a focus on the theoretical aspects of determining the causal order among variables.
no code implementations • 26 Oct 2022 • Maximilian Kertel, Stefan Harmeling, Markus Pauly
Many production processes are characterized by numerous and complex cause-and-effect relationships.
no code implementations • 14 Jan 2022 • Maximilian Kertel, Markus Pauly
In this work we present a rigorous application of the Expectation Maximization algorithm to determine the marginal distributions and the dependence structure in a Gaussian copula model with missing data.