Frozen HSL features as a DDPM conditioning substrate. Reproducible feasibility run with matched controls and retained negative results; not SOTA.
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Updated
Jul 17, 2026 - Python
Frozen HSL features as a DDPM conditioning substrate. Reproducible feasibility run with matched controls and retained negative results; not SOTA.
Deterministic, non-learned byte-to-HSL signal encoder for PyTorch: 27-D interpretable features, lossless byte codec, tests, controls, and GPU paths.
First-Principles Cosmological Architecture by Marco Lindenbeck
PyTorch transformer input from raw bytes with zero learned input parameters: no tokenizer, embedding table, or learned input projection.
ARCHIVE CANONIQUE — corpus P0–P48 : opérateur de verdict à zéro paramètre, série A (méthode), méta-chantiers M1/M1b (postulat central mesuré, réfuté avec inversion), registre de 20 frontières mesurées (10 fermées / 4 ouvertes / 6 partielles), SHASUMS complet, release Allen Cell Types. B3-FAIL publiés.
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