1 citations · 1 across the 1 of their papers we have counts for
4 papers
Learning optimal policies from event logs through reinforcement learning: a comparison of deep and MDP-based approaches
Stefano Branchi, Andrei Buliga, Chiara Di Francescomarino +4
Prescriptive Process Monitoring is an emerging area within Process Mining that focuses on recommending actions to optimize business outcomes. Most existing works prescribe pre-defi…
Graph-based Event Log Repair
Sebastiano Dissegna, Chiara Di Francescomarino, Massimiliano Ronzani
The quality of event logs in Process Mining is crucial when applying any form of analysis to them. In real-world event logs, the acquisition of data can be non-trivial (e.g., due t…
Generating Counterfactual Explanations Under Temporal Constraints
Andrei Buliga, Chiara Di Francescomarino, Chiara Ghidini +2
Counterfactual explanations are one of the prominent eXplainable Artificial Intelligence (XAI) techniques, and suggest changes to input data that could alter predictions, leading t…
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…