logbook.json

{
  "schema_version": 1,
  "title": "Repro: Nested birth-death processes are competitive with neural networks as time-dependent models of protein evolution",
  "emoji": "🎯",
  "space_id": "latticetower/nested-tkf-repro",
  "paper": {
    "arxiv_id": null,
    "openreview_id": "qs9lQluekx",
    "biorxiv_doi": "10.64898/2026.02.02.702952"
  },
  "tags": [
    "icml2026-repro",
    "paper-qs9lQluekx"
  ],
  "updated_at": "2026-07-17T02:53:51+00:00",
  "root": {
    "slug": "index",
    "title": "Repro: Nested birth-death processes are competitive with neural networks as time-dependent models of protein evolution",
    "file": "pages/index.md",
    "children": [
      {
        "slug": "claim-1-nested-tkf-model-30k-params-is-highly-competitive-with-neural-networks-tens-of-millions-of-params",
        "title": "Claim 1: Nested TKF model (30K params) is highly competitive with neural networks (tens of millions of params)",
        "file": "pages/claim-1-nested-tkf-model-30k-params-is-highly-competitive-with-neural-networks-tens-of-millions-of-params/page.md",
        "children": []
      },
      {
        "slug": "claim-2-mixdom-outperforms-all-but-two-neural-architectures-on-pfam",
        "title": "Claim 2: MixDom outperforms all but two neural architectures on PFam",
        "file": "pages/claim-2-mixdom-outperforms-all-but-two-neural-architectures-on-pfam/page.md",
        "children": []
      },
      {
        "slug": "conclusion",
        "title": "Conclusion",
        "file": "pages/conclusion/page.md",
        "children": []
      }
    ]
  },
  "agent_view_tokens": 9542,
  "revision": "1784256831583199000"
}