{
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  "Date": "2025-12-07",
  "Title": "Hopfield Artificial Neural Networks",
  "Authors@R": "c(person(\"Emmanuel\", \"Paradis\", role = c(\"aut\", \"cre\", \"cph\"), email = \"Emmanuel.Paradis@ird.fr\", comment = c(ORCID = \"0000-0003-3092-2199\")))",
  "Description": "Builds and optimizes Hopfield artificial neural networks\n(Hopfield, 1982, <doi:10.1073/pnas.79.8.2554>). One-layer and\nthree-layer models are implemented. The energy of the Hopfield\nnetwork is minimized with formula from Krotov and Hopfield\n(2016, <doi:10.48550/ARXIV.1606.01164>). Optimization\n(supervised learning) is done through a gradient-based method.\nClassification is done with S3 methods predict().\nParallelization with 'OpenMP' is used if available during\ncompilation.",
  "URL": "https://github.com/emmanuelparadis/hann",
  "BugReports": "https://github.com/emmanuelparadis/hann/issues",
  "License": "GPL-3",
  "Repository": "https://emmanuelparadis.r-universe.dev",
  "Date/Publication": "2026-01-06 20:03:44 UTC",
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    "User": "root"
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      "title": "Hopfield Artificial Neural Networks",
      "topics": [
        "hann-package"
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    {
      "page": "binarize",
      "title": "Helper Function to Prepare Data From Images",
      "topics": [
        "binarize"
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    },
    {
      "page": "buildSigma",
      "title": "Hopfield Network Energy",
      "topics": [
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    },
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      "page": "combine",
      "title": "Combine Several Neural Nets for Prediction",
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      "title": "Parameters for Neural Network Optimization",
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      "title": "Method Top-Level Functions",
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        "fitted.hann",
        "hann",
        "labels.hann",
        "plot.hann",
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