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Sven Weinzierl
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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
752020
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
552020
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
332020
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
302020
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
212020
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
202020
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
192020
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
182020
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
172021
Exploring Gated Graph Sequence Neural Networks for Predicting Next Process Activities
S Weinzierl
5th International Workshop on Artificial Intelligence for Business Process …, 2021
172021
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
172021
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
172020
Pedictive Business Process Monitoring with Context Information from Documents
S Weinzierl, KC Revoredo, M Matzner
27th European Conference on Information Systems (ECIS2019), 2019
15*2019
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
142022
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
102022
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
82023
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
62021
Predictive Business Process Deviation Monitoring
S Weinzierl, S Dunzer, J Tenschert, S Zilker, M Matzner
29th European Conference on Information Systems (ECIS2021), 2021
62021
Text-aware predictive process monitoring with contextualized word embeddings
L Cabrera, S Weinzierl, S Zilker, M Matzner
International Conference on Business Process Management, 303-314, 2022
52022
Interpretable generalized additive neural networks
M Kraus, D Tschernutter, S Weinzierl, P Zschech
European Journal of Operational Research, 2023
32023
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