logbook.json

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  "title": "Repro: High-accuracy sampling for diffusion models and log-concave distributions",
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  "paper": {
    "arxiv_id": "2602.01338"
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    "title": "Repro: High-accuracy sampling for diffusion models and log-concave distributions",
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        "slug": "claim-1-delta-error-in-polylog-1-delta-steps-exponential-improvement",
        "title": "Claim 1: delta-error in polylog(1/delta) steps (exponential improvement)",
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        "children": []
      },
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        "slug": "claim-2-complexity-o-d-star-polylog-1-delta-under-minimal-assumptions",
        "title": "Claim 2: complexity O~(d_star polylog(1/delta)) under minimal assumptions",
        "file": "pages/claim-2-complexity-o-d-star-polylog-1-delta-under-minimal-assumptions/page.md",
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        "title": "Claim 3: first polylog(1/delta) log-concave sampler using only gradient evals",
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      {
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        "title": "Conclusion",
        "file": "pages/conclusion/page.md",
        "children": []
      },
      {
        "slug": "high-accuracy-sampling-repro",
        "title": "high-accuracy-sampling-repro",
        "file": "pages/high-accuracy-sampling-repro/page.md",
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      },
      {
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        "title": "Operator decisions",
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      },
      {
        "slug": "claim-4-non-uniform-lipschitz-condition-refines-the-complexity-theorem-4-9",
        "title": "Claim 4: non-uniform Lipschitz condition refines the complexity (Theorem 4.9)",
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