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cs.LG2026
Probabilistic Forecasting of Business Process Executions with Neural Temporal Point Processes
Jiaxin Yuan, Daniela Grigori, Han van der Aa
Operators of service-based systems act on forecasts of how a running execution will continue, and such a forecast is actionable only if its reliability is known. Mainstream deep-le…
cs.LG2024★ 1 cited
PGTNet: A Process Graph Transformer Network for Remaining Time Prediction of Business Process Instances
Keyvan Amiri Elyasi, Han van der Aa, Heiner Stuckenschmidt
We present PGTNet, an approach that transforms event logs into graph datasets and leverages graph-oriented data for training Process Graph Transformer Networks to predict the remai…