Current and Upcoming Projects

Start: 2025-03-01
End: 2028-02-29
Principal Investigators: Roland Herzog, Markus Richter
Staff: Viktor Martinek, Ophelia Frotscher
Funded by: DFG within the Priority Program funding scheme
Part of: Machine Learning in Chemical Engineering (SPP 2331)

Recent Completed Projects

Start: 2022-02-01
End: 2025-02-28
Principal Investigators: Roland Herzog, Markus Richter
Staff: Viktor Martinek, Ophelia Frotscher
Funded by: DFG within the Priority Program funding scheme
Part of: Machine Learning in Chemical Engineering (SPP 2331)

Latest Publications

• Roland Herzog and Viktor Martinek
  Machine learning for thermodynamic property modeling
  Oberwolfach Reports, 2026
  
  doi:10.4171/owr/2026/26
  bibtex

  @ARTICLE{HerzogMartinek:2026:1,
    AUTHOR = {Herzog, Roland and Martinek, Viktor},
    EDITOR = {Ghattas, Omar and Heinkenschloss, Matthias and Reich, Sebastian and Schillings, Claudia},
    PUBLISHER = {European Mathematical Society Publishing House},
    BOOKTITLE = {Workshop: Mathematical Foundation of Digital Twins},
    DATE = {2026-08},
    DOI = {10.4171/owr/2026/26},
    JOURNALTITLE = {Oberwolfach Reports},
    TITLE = {Machine learning for thermodynamic property modeling},
  }

• Viktor Martinek and Roland Herzog
  Symbolic regression for shared expressions – introducing partial parameter sharing
  Parallel Problem Solving from Nature – PPSN XIX, p.251-266, 2026
  
  arXiv:2601.04051
  doi:10.1007/978-3-032-36229-2_16
  bibtex

  @INPROCEEDINGS{MartinekHerzog:2026:2,
    AUTHOR = {Martinek, Viktor and Herzog, Roland},
    PUBLISHER = {Springer Nature Switzerland},
    BOOKTITLE = {Parallel Problem Solving from Nature – PPSN XIX},
    DATE = {2026-08},
    DOI = {10.1007/978-3-032-36229-2_16},
    EPRINT = {2601.04051},
    EPRINTTYPE = {arXiv},
    PAGES = {251--266},
    TITLE = {Symbolic regression for shared expressions – introducing partial parameter sharing},
  }

• Viktor Martinek, Marco Drache, Frederic Matussek, Moritz Baumert, Lennart Arendes, Jelena Fiosina, Ophelia Frotscher, Roland Herzog and Sabine Beuermann
  A shared expression to predict monomer consumption in itaconate--acrylate radical copolymerizations developed with symbolic regression, 2026
  
  doi:10.26434/chemrxiv.15005769/v1
  bibtex

  @ONLINE{MartinekDracheMatussekBaumertArendesFiosinaFrotscherHerzogBeuermann:2026:1,
    AUTHOR = {Martinek, Viktor and Drache, Marco and Matussek, Frederic and Baumert, Moritz and Arendes, Lennart and Fiosina, Jelena and Frotscher, Ophelia and Herzog, Roland and Beuermann, Sabine},
    PUBLISHER = {American Chemical Society (ACS)},
    DATE = {2026-07},
    DOI = {10.26434/chemrxiv.15005769/v1},
    TITLE = {A shared expression to predict monomer consumption in itaconate--acrylate radical copolymerizations developed with symbolic regression},
  }

• Viktor Martinek, Julia Reuter, Ophelia Frotscher, Sanaz Mostaghim, Markus Richter and Roland Herzog
  Shape constraints in symbolic regression using penalized least squares
  Machine Learning and Principles and Practice of Knowledge Discovery in Databases, p.224-239, 2026
  
  arXiv:2405.20800
  doi:10.1007/978-3-032-25305-7_16
  bibtex

  @INBOOK{MartinekReuterFrotscherMostaghimRichterHerzog:2026:1,
    AUTHOR = {Martinek, Viktor and Reuter, Julia and Frotscher, Ophelia and Mostaghim, Sanaz and Richter, Markus and Herzog, Roland},
    EDITOR = {Cerrato, Mattia and Kalinauskaitė, Danguolė and Lukoševičius, Mantas and Pechenizkiy, Mykola and Šutienė, Kristina},
    PUBLISHER = {Springer Nature Switzerland},
    BOOKTITLE = {Machine Learning and Principles and Practice of Knowledge Discovery in Databases},
    DATE = {2026-05},
    DOI = {10.1007/978-3-032-25305-7_16},
    EPRINT = {2405.20800},
    EPRINTTYPE = {arXiv},
    PAGES = {224--239},
    TITLE = {Shape constraints in symbolic regression using penalized least squares},
  }

Latest Software

• Viktor Martinek
  Fast symbolic regression benchmarking, 2025
  
  doi:10.5281/zenodo.15469873
  https://github.com/viktmar/FastSRB/
  bibtex

  @SOFTWARE{Martinek:2025:1,
    AUTHOR = {Martinek, Viktor},
    URL = {https://github.com/viktmar/FastSRB/},
    DATE = {2025},
    DOI = {10.5281/zenodo.15469873},
    TITLE = {Fast symbolic regression benchmarking},
  }

• Viktor Martinek
  Thermodynamics-informed symbolic regression (TiSR). A tool for the thermodynamic equation of state development, 2023
  
  doi:10.5281/zenodo.8317546
  https://github.com/scoop-group/TiSR/
  bibtex

  @SOFTWARE{Martinek:2023:1,
    AUTHOR = {Martinek, Viktor},
    URL = {https://github.com/scoop-group/TiSR/},
    DATE = {2023},
    DOI = {10.5281/zenodo.8317546},
    TITLE = {Thermodynamics-informed symbolic regression (TiSR). A tool for the thermodynamic equation of state development},
  }

Recent Teaching

• 2024 SS
  Mathematical Machine Learning (Seminar)

Currently Supervising

• M.Sc. Thesis of Mara-Eliana Popescu:
  Denoising Equations: Continuous and Discrete Diffusion Models for Symbolic Regression
  M.Sc. Data and Computer Science, Heidelberg University
  Supervision: Ullrich Köthe, Roland Herzog, Paul Sägert and Viktor Martinek