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repro-deep-flow-networks
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{
  "schema_version": 2,
  "title": "Reproduction: Deep Flow Networks",
  "emoji": "🎯",
  "space_id": "nmaher/repro-deep-flow-networks",
  "paper": null,
  "tags": [
    "icml2026-repro",
    "paper-Z7rhDaBvBo"
  ],
  "updated_at": "2026-07-25T09:46:24+00:00",
  "root": {
    "slug": "index",
    "title": "Reproduction: Deep Flow Networks",
    "file": "pages/index.md",
    "children": [
      {
        "slug": "executive-summary",
        "title": "Executive summary",
        "file": "pages/executive-summary/page.md",
        "children": []
      },
      {
        "slug": "claim-1-dfns-are-universal-approximators-of-convex-extendible-discrete-functions",
        "title": "Claim 1: DFNs are universal approximators of convex-extendible discrete functions",
        "file": "pages/claim-1-dfns-are-universal-approximators-of-convex-extendible-discrete-functions/page.md",
        "children": []
      },
      {
        "slug": "claim-2-strong-approximation-accuracy-substantially-faster-integer-optimization",
        "title": "Claim 2: Strong approximation accuracy, substantially faster integer optimization",
        "file": "pages/claim-2-strong-approximation-accuracy-substantially-faster-integer-optimization/page.md",
        "children": []
      },
      {
        "slug": "conclusion",
        "title": "Conclusion",
        "file": "pages/conclusion/page.md",
        "children": []
      }
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