13 citations · 31 across the 6 of their papers we have counts for
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cs.DB2024★ 6 cited
Generating the Traces You Need: A Conditional Generative Model for Process Mining Data
Riccardo Graziosi, Massimiliano Ronzani, Andrei Buliga +5
In recent years, trace generation has emerged as a significant challenge within the Process Mining community. Deep Learning (DL) models have demonstrated accuracy in reproducing th…
cs.AI2024★ 6 cited
Guiding the generation of counterfactual explanations through temporal background knowledge for Predictive Process Monitoring
Andrei Buliga, Chiara Di Francescomarino, Chiara Ghidini +2
Counterfactual explanations suggest what should be different in the input instance to change the outcome of an AI system. When dealing with counterfactual explanations in the field…