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This technical report tries to fill a gap in current literature on TimescaleGraphical Event Models. I propose and evaluate different heuristics todetermine hyper-parameters during the structure learning algorithm and refinean existing distance measure. A comprehensive benchmark on synthetic data willbe conducted allowing conclusions about the applicability of the differentheuristics.

Learnability of Timescale Graphical Event Models