Dr. Sven Weinzierl

Lehrstuhl für Digital Industrial Service Systems

Predictive business process deviation monitoring (2021) Weinzierl S, Dunzer S, Tenschert J, Zilker S, Matzner M Conference contribution, Original article Bringing light into the darkness - A systematic literature review on explainable predictive business process monitoring techniques (2021) Stierle M, Brunk J, Weinzierl S, Zilker S, Matzner M, Becker J Conference contribution, Original article Time matters: Time-aware LSTMs for predictive business process monitoring (2020) Nguyen A, Chatterjee S, Weinzierl S, Schwinn L, Matzner M, Eskofier B Conference contribution, Conference Contribution Prescriptive business process monitoring for recommending next best actions (2020) Weinzierl S, Dunzer S, Zilker S, Matzner M Conference contribution, Original article Exploring the effect of context information on deep learning business process predictions (2020) Brunk J, Stottmeister J, Weinzierl S, Matzner M, Becker J Journal article, Original article Explainable predictive business process monitoring using gated graph neural networks (2020) Harl M, Weinzierl S, Stierle M, Matzner M Journal article, Original article XNAP: Making LSTM-based next activity predictions explainable by using LRP (2020) Weinzierl S, Zilker S, Brunk J, Revoredo K, Matzner M, Becker J Conference contribution, Conference Contribution Detecting workarounds in business processes — A deep learning method for analyzing event logs (2020) Weinzierl S, Wolf V, Pauli T, Beverungen D, Matzner M Conference contribution, Conference Contribution Closing the gap between smart manufacturing applications and data management (2020) Marx E, Stierle M, Weinzierl S, Matzner M Conference contribution, Conference Contribution From predictive to prescriptive process monitoring: Recommending the next best actions instead of calculating the next most likely events (2020) Weinzierl S, Zilker S, Stierle M, Park G, Matzner M Conference contribution, Conference Contribution