publications

2024

1. Towards automated business process redesign in runtime using generative machine learning

   Maximilian Victor Harl, Sandra Zilker, and Sven Weinzierl

   2024

   Bib

   @article{harl2024towards,
     title = {Towards automated business process redesign in runtime using generative machine learning},
     author = {Harl, Maximilian Victor and Zilker, Sandra and Weinzierl, Sven},
     year = {2024},
   }

2. A Comparative Review of Descriptive Process Models in Healthcare Operations Management and Analytics

   Isabella Eigner^*, Maximilian Harl^*, and Daniel Neumann^*

   Dimensions of Intelligent Analytics for Smart Digital Health Solutions, 2024

   Bib

   @article{eigner2024comparative,
     title = {A Comparative Review of Descriptive Process Models in Healthcare Operations Management and Analytics},
     author = {Eigner, Isabella and Harl, Maximilian and Neumann, Daniel},
     journal = {Dimensions of Intelligent Analytics for Smart Digital Health Solutions},
     year = {2024},
     pages = {153--188},
     publisher = {Chapman and Hall/CRC},
   }

2023

1. Fully Automated Business Process Redesign

   Maximilian V. Harl

   Master Thesis in International Information Systems, 2023

   In publication. Not available yet.

   Bib

   @thesis{harl2023,
     author = {Harl, Maximilian V.},
     title = {Fully Automated Business Process Redesign},
     year = {2023},
     school = {Master Thesis in International Information Systems},
     note = {In publication. Not available yet.},
   }

2. Network medicine-based epistasis detection in complex diseases: ready for quantum computing

   Markus Hoffmann^*, Julian M Poschenrieder^*, Massimiliano Incudini^*, and 8 more authors

   Medrxiv, 2023

   Bib Code

   @article{hoffmann2023network,
     title = {Network medicine-based epistasis detection in complex diseases: ready for quantum computing},
     author = {Hoffmann, Markus and Poschenrieder, Julian M and Incudini, Massimiliano and Baier, Sylvie and Fitz, Amelie and Maier, Andreas and Hartung, Michael and Hoffmann, Christian and Trummer, Nico and Adamowicz, Klaudia and others},
     year = {2023},
     journal = {Medrxiv},
     publisher = {Cold Spring Harbor Laboratory Preprints},
   }

2022

1. A light in the dark: deep learning practices for industrial computer vision

   Maximilian Harl, Marvin Herchenbach, Sven Kruschel, and 3 more authors

   arXiv preprint arXiv:2201.02028, 2022

   Bib Code

   @article{harl2022light,
     title = {A light in the dark: deep learning practices for industrial computer vision},
     author = {Harl, Maximilian and Herchenbach, Marvin and Kruschel, Sven and Hambauer, Nico and Zschech, Patrick and Kraus, Mathias},
     journal = {arXiv preprint arXiv:2201.02028},
     year = {2022},
   }

2021

1. A technique for determining relevance scores of process activities using graph-based neural networks

   Matthias Stierle, Sven Weinzierl, Maximilian Harl, and 1 more author

   Decision Support Systems, 2021

   Bib Code

   @article{stierle2021technique,
     title = {A technique for determining relevance scores of process activities using graph-based neural networks},
     author = {Stierle, Matthias and Weinzierl, Sven and Harl, Maximilian and Matzner, Martin},
     journal = {Decision Support Systems},
     volume = {144},
     pages = {113511},
     year = {2021},
     publisher = {Elsevier},
   }

2020

1. Explainable predictive business process monitoring using gated graph neural networks

   Maximilian Harl, Sven Weinzierl, Mathias Stierle, and 1 more author

   Journal of Decision Systems, 2020

   Bib

   @article{harl2020explainable,
     title = {Explainable predictive business process monitoring using gated graph neural networks},
     author = {Harl, Maximilian and Weinzierl, Sven and Stierle, Mathias and Matzner, Martin},
     journal = {Journal of Decision Systems},
     volume = {29},
     number = {sup1},
     pages = {312--327},
     year = {2020},
     publisher = {Taylor \& Francis},
   }

2019

1. Explainable Predictive Process Monitoring: An evaluation of Gated Graph Neural Network as a white-box classification model

   Maximilian V. Harl

   Bachelor Thesis in Information Systems, 2019

   Available upon request.

   Bib Code

   @thesis{harl2019,
     author = {Harl, Maximilian V.},
     title = {Explainable Predictive Process Monitoring: An evaluation of Gated Graph Neural Network as a white-box classification model},
     year = {2019},
     school = {Bachelor Thesis in Information Systems},
     note = {Available upon request.},
   }