Sven Weinzierl

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Martin MatznerFriedrich-Alexander-Universität Erlangen-Nürnberg (FAU)Verified email at fau.de
Sandra ZilkerFriedrich-Alexander-Universität Erlangen-NürnbergVerified email at fau.de
Matthias StierleResearcher, Friedrich-Alexander Universität Erlangen-NürnbergVerified email at fau.de
Jörg BeckerFull Professor of Information Systems, University of MünsterVerified email at ercis.uni-muenster.de
Kate RevoredoResearch Associate at Humboldt-Universität zu BerlinVerified email at hu-berlin.de
Jens BrunkEuropean Research Center for Information Systems (ERCIS), University of MünsterVerified email at ercis.uni-muenster.de
Maximilian V. HarlStudent of Neuroscience, Bioinformatics, and Information Systems at ETH/UZH, TUM/LMU, and FAUVerified email at fau.de
Sebastian DunzerResearcher, Chair for Digital Industrial Service Systems, Friedrich-Alexander-Unviversität Erlangen-NürnbergVerified email at fau.de
Daniel BeverungenProf. Dr., Paderborn UniversityVerified email at uni-paderborn.de
An NguyenFriedrich-Alexander University Erlangen-Nürnberg (FAU)Verified email at fau.de
Bjoern M. EskofierMachine Learning and Data Analytics Lab, Friedrich-Alexander-Universität Erlangen-NürnbergVerified email at fau.de
Verena WolfPaderborn UniversityVerified email at uni-paderborn.de
Tobias PauliFAU Erlangen-NürnbergVerified email at fau.de
Patrick ZschechFriedrich-Alexander-Universität Erlangen-NürnbergVerified email at fau.de
Mathias KrausFAU Erlangen-NurembergVerified email at fau.de
Leo SchwinnPostdoc @ Friedrich-Alexander Universität Erlangen NürnbergVerified email at fau.de
Gyunam ParkPh.D. Candidate, PADS (chair of Process and Data Science), Computer Science, RWTH-Aachen UniversityVerified email at pads.rwth-aachen.de
Patrick DelfmannUniversity of Koblenz-LandauVerified email at uni-koblenz.de
Christoph DrodtUniversity of Koblenz-LandauVerified email at uni-koblenz.de
Nico HambauerFriedrich-Alexander-Universität Erlangen-NürnbergVerified email at fau.de

Sven Weinzierl

Researcher, Friedrich-Alexander-Universität Erlangen-Nürnberg

Verified email at fau.de

Business Process Management Deep Learning Machine Learning Business Analytics


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Explainable predictive business process monitoring using gated graph neural networks M Harl, S Weinzierl, M Stierle, M Matzner Journal of Decision Systems 29 (sup1), 312-327, 2020	63	2020
Prescriptive Business Process Monitoring for Recommending Next Best Actions S Weinzierl, S Dunzer, S Zilker, M Matzner 18th International Conference on Business Process Management (BPMForum2020), 2020	50	2020
XNAP: Making LSTM-Based Next Activity Predictions Explainable by Using LRP S Weinzierl, S Zilker, J Brunk, K Revoredo, M Matzner, J Becker 4th International Workshop on Artificial Intelligence for Business Process …, 2020	27	2020
Time Matters: Time-Aware LSTMs for Predictive Business Process Monitoring A Nguyen, S Chatterjee, S Weinzierl, L Schwinn, M Matzner, B Eskofier 1st International Workshop on Leveraging Machine Learning in Process Mining …, 2020	25	2020
Exploring the effect of context information on deep learning business process predictions J Brunk, J Stottmeister, S Weinzierl, M Matzner, J Becker Journal of Decision Systems 29 (sup1), 328-343, 2020	20	2020
A next click recommender system for web-based service analytics with context-aware LSTMs S Weinzierl, M Stierle, S Zilker, M Matzner 53rd Hawaii International Conference on System Sciences (HICSS2020), 2020	19	2020
An empirical comparison of deep-neural-network architectures for next activity prediction using context-enriched process event logs S Weinzierl, S Zilker, J Brunk, K Revoredo, A Nguyen, M Matzner, ... arXiv preprint arXiv:2005.01194, 2020	18	2020
From predictive to prescriptive process monitoring: Recommending the next best actions instead of calculating the next most likely events S Weinzierl, S Zilker, M Stierle, G Park, M Matzner 15th International Conference on Wirtschaftsinformatik (WI2020), 2020	17	2020
Detecting Workarounds in Business Processes -- a Deep Learning method for Analyzing Event Logs. S Weinzierl, V Wolf, T Pauli, D Beverungen, M Matzner 28th European Conference on Information Systems (ECIS2020), 2020	16	2020
Exploring Gated Graph Sequence Neural Networks for Predicting Next Process Activities S Weinzierl 5th International Workshop on Artificial Intelligence for Business Process …, 2021	13	2021
Bringing Light Into the Darkness-A Systematic Literature Review on Explainable Predictive Business Process Monitoring Techniques M Stierle, J Brunk, S Weinzierl, S Zilker, M Matzner, J Becker 29th European Conference on Information Systems (ECIS2021), 2021	13	2021
Detecting temporal workarounds in business processes–A deep-learning-based method for analysing event log data S Weinzierl, V Wolf, T Pauli, D Beverungen, M Matzner Journal of Business Analytics 5 (1), 76-100, 2022	12	2022
A technique for determining relevance scores of process activities using graph-based neural networks M Stierle, S Weinzierl, M Harl, M Matzner Decision Support Systems 144, 113511, 2021	12	2021
Pedictive Business Process Monitoring with Context Information from Documents S Weinzierl, KC Revoredo, M Matzner 27th European Conference on Information Systems (ECIS2019), 2019	11*	2019
GAM (e) changer or not? An evaluation of interpretable machine learning models based on additive model constraints P Zschech, S Weinzierl, N Hambauer, S Zilker, M Kraus 30th European Conference on Information Systems (ECIS2022), 2022	8	2022
Predictive end-to-end enterprise process network monitoring F Oberdorf, M Schaschek, S Weinzierl, N Stein, M Matzner, CM Flath Business & Information Systems Engineering 65 (1), 49-64, 2023	5	2023
The Recomminder: A Decision Support Tool for Predictive Business Process Monitoring C Drodt, S Weinzierl, M Matzner, P Delfmann Business Process Management Demonstration Track (BPMDemo2021), 2021	5	2021
Predictive Business Process Deviation Monitoring S Weinzierl, S Dunzer, J Tenschert, S Zilker, M Matzner 29th European Conference on Information Systems (ECIS2021), 2021	4	2021
Guiding Text-to-Text Privatization by Syntax S Arnold, D Yesilbas, S Weinzierl arXiv preprint arXiv:2306.01471, 2023	1	2023
Driving Context into Text-to-Text Privatization S Arnold, D Yesilbas, S Weinzierl arXiv preprint arXiv:2306.01457, 2023	1	2023

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