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[Re] Learning Neural PDE Solvers with Convergence Guarantees ICLR Reproducibility Challenge 2019

Francesco Bardi; Samuel von Baussnern; Emiljano Gjiriti


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{
  "description": "Replication", 
  "license": "http://creativecommons.org/licenses/by/4.0/legalcode", 
  "creator": [
    {
      "@type": "Person", 
      "name": "Francesco Bardi"
    }, 
    {
      "@type": "Person", 
      "name": "Samuel von Baussnern"
    }, 
    {
      "@type": "Person", 
      "name": "Emiljano Gjiriti"
    }
  ], 
  "url": "https://zenodo.org/record/3162890", 
  "image": "https://zenodo.org/static/img/logos/zenodo-gradient-round.svg", 
  "contributor": [
    {
      "@type": "Person", 
      "name": "Koustuv Sinha"
    }, 
    {
      "@type": "Person", 
      "name": "Anonymous reviewers"
    }
  ], 
  "datePublished": "2019-05-22", 
  "headline": "[Re] Learning Neural PDE Solvers with Convergence Guarantees ICLR Reproducibility Challenge 2019", 
  "keywords": [
    "PDE", 
    "PDE Solver", 
    "Deep Learning", 
    "Python", 
    "PyTorch"
  ], 
  "@context": "https://schema.org/", 
  "identifier": "https://doi.org/10.5281/zenodo.3162890", 
  "@id": "https://doi.org/10.5281/zenodo.3162890", 
  "@type": "ScholarlyArticle", 
  "name": "[Re] Learning Neural PDE Solvers with Convergence Guarantees ICLR Reproducibility Challenge 2019"
}
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