@phdthesis{Mueller2009,
  author    = {M{\"u}ller, Falk},
  title     = {Deliktische Schadensersatzanspr{\"u}che von mittelbar gesch{\"a}digten Personen im Falle einer t{\"o}dlichen Verletzung im deutschen und amerikanischen Recht},
  series = {Europ{\"a}ische Hochschulschriften : Reihe 2, Rechtswissenschaft},
  volume    = {4838},
  journal   = {Europ{\"a}ische Hochschulschriften : Reihe 2, Rechtswissenschaft},
  publisher = {Lang},
  address   = {Frankfurt am Main},
  isbn      = {978-3-631-58291-6},
  pages     = {416 S.},
  year      = {2009},
  language  = {de}
}
@article{MuellerZechHesse2021,
  author    = {M{\"u}ller, Sebastian and Zech, Alraune and Hesse, Falk},
  title     = {ogs5py: APython-APIfor theOpenGeoSys5 Scientific Modeling Package},
  series = {Groundwater : journal of the Association of Ground-Water Scientists and Engineers, a division of the National Ground Water Association},
  volume    = {59},
  journal   = {Groundwater : journal of the Association of Ground-Water Scientists and Engineers, a division of the National Ground Water Association},
  number    = {1},
  publisher = {Wiley},
  address   = {Hoboken},
  issn      = {0017-467X},
  doi       = {10.1111/gwat.13017},
  pages     = {117 -- 122},
  year      = {2021},
  abstract  = {High-performance numerical codes are an indispensable tool for hydrogeologists when modeling subsurface flow and transport systems. But as they are written in compiled languages, like C/C++ or Fortran, established software packages are rarely user-friendly, limiting a wider adoption of such tools. OpenGeoSys (OGS), an open-source, finite-element solver for thermo-hydro-mechanical-chemical processes in porous and fractured media, is no exception. Graphical user interfaces may increase usability, but do so at a dramatic reduction of flexibility and are difficult or impossible to integrate into a larger workflow. Python offers an optimal trade-off between these goals by providing a highly flexible, yet comparatively user-friendly environment for software applications. Hence, we introduceogs5py, a Python-API for the OpenGeoSys 5 scientific modeling package. It provides a fully Python-based representation of an OGS project, a large array of convenience functions for users to interact with OGS and connects OGS to the scientific and computational environment of Python.},
  language  = {en}
}
@article{MuellerSchuelerZechetal.2022,
  author    = {M{\"u}ller, Sebastian and Sch{\"u}ler, Lennart and Zech, Alraune and Heße, Falk},
  title     = {GSTools v1.3: a toolbox for geostatistical modelling in Python},
  series = {Geoscientific model development : an interactive open access journal of the European Geosciences Union},
  volume    = {15},
  journal   = {Geoscientific model development : an interactive open access journal of the European Geosciences Union},
  number    = {7},
  publisher = {Copernicus},
  address   = {G{\"o}ttingen},
  issn      = {1991-959X},
  doi       = {10.5194/gmd-15-3161-2022},
  pages     = {3161 -- 3182},
  year      = {2022},
  abstract  = {Geostatistics as a subfield of statistics accounts for the spatial correlations encountered in many applications of, for example, earth sciences. Valuable information can be extracted from these correlations, also helping to address the often encountered burden of data scarcity. Despite the value of additional data, the use of geostatistics still falls short of its potential. This problem is often connected to the lack of user-friendly software hampering the use and application of geostatistics. We therefore present GSTools, a Python-based software suite for solving a wide range of geostatistical problems. We chose Python due to its unique balance between usability, flexibility, and efficiency and due to its adoption in the scientific community. GSTools provides methods for generating random fields; it can perform kriging, variogram estimation and much more. We demonstrate its abilities by virtue of a series of example applications detailing their use.},
  language  = {en}
}