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pymor/pymor: pyMOR 2020.2.0

Stephan Rave; Petar Mlinarić; Tim Keil; Felix Schindler; Hendrik Kleikamp; Michael Laier; Andreas Buhr; Michael Schaefer; G. D. McBain; Julia Brunken; Meret Behrens; Luca Mechelli; cabuze


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{
  "publisher": "Zenodo", 
  "DOI": "10.5281/zenodo.4314785", 
  "title": "pymor/pymor: pyMOR 2020.2.0", 
  "issued": {
    "date-parts": [
      [
        2020, 
        12, 
        10
      ]
    ]
  }, 
  "abstract": "<p>pyMOR is a software library for building model order reduction\napplications with the Python programming language. Implemented\nalgorithms include reduced basis methods for parametric linear and\nnon-linear problems, as well as system-theoretic methods such as\nbalanced truncation or IRKA. All algorithms in pyMOR are formulated in\nterms of abstract interfaces for seamless integration with external PDE\nsolver packages. Moreover, pure Python implementations of finite element\nand finite volume discretizations using the NumPy/SciPy scientific\ncomputing stack are provided for getting started quickly.</p>\n<p>Highlights of this release are:</p>\n<ul>\n<li>Parameter derivatives of solutions and outputs</li>\n<li>Neural network reductor for non-stationary problems</li>\n<li>New tutorials</li>\n</ul>\n<p>You can read the full release notes at <a href=\"https://docs.pymor.org/2020.2.0/release_notes/all.html\">https://docs.pymor.org/2020.2.0/release_notes/all.html</a></p>", 
  "author": [
    {
      "family": "Stephan Rave"
    }, 
    {
      "family": "Petar Mlinari\u0107"
    }, 
    {
      "family": "Tim Keil"
    }, 
    {
      "family": "Felix Schindler"
    }, 
    {
      "family": "Hendrik Kleikamp"
    }, 
    {
      "family": "Michael Laier"
    }, 
    {
      "family": "Andreas Buhr"
    }, 
    {
      "family": "Michael Schaefer"
    }, 
    {
      "family": "G. D. McBain"
    }, 
    {
      "family": "Julia Brunken"
    }, 
    {
      "family": "Meret Behrens"
    }, 
    {
      "family": "Luca Mechelli"
    }, 
    {
      "family": "cabuze"
    }
  ], 
  "version": "2020.2.0", 
  "type": "article", 
  "id": "4314785"
}
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