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  "paper": {
    "arxiv_id": "1711.10561",
    "title": "Physics Informed Deep Learning (Part I): Data-driven Solutions of Nonlinear Partial Differential Equations",
    "authors": [
      "Maziar Raissi",
      "Paris G. Perdikaris",
      "George Em Karniadakis"
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    "year": 2017,
    "doi": null,
    "venue": null,
    "openalex_id": "https://openalex.org/W2772097715"
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  "summary": "Running the authors Burgers.py (the earliest version in their repository, from five months after arXiv v1) with its fixed seeds on CPU gives a relative L2 error of 2.15e-3 for the continuous-time Burgers example, against 6.7e-4 reported. That meets the pre-registered order-of-magnitude headline check (at most 6.7e-3) but not the stricter within-a-factor-of-2 check. The paper own Table 1 shows errors varying between 1e-4 and 1e-2 across neighbouring settings, and this run used a CPU rather than the reported GPU. The Table 1 sweep was not run.",
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      "text": "Code availability: the repository linked in the paper was created on 2018-01-20, about two months after arXiv v1 (2017-11-28), and the Burgers code first appears on 2018-05-01 (commit 13ce051). The code tested therefore postdates the paper version by five months; no earlier code exists."
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  "right_of_reply": "Authors may submit a response, which is published alongside this report unedited."
}