Hidden-State–Driven Survival Modeling with Mamba

Zenodo (CERN European Organization for Nuclear Research) 2026 Open access

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Authors: K.D. Pom
DOI: 10.5281/zenodo.18251548
Cited by: 0

Abstract

This release provides an early public disclosure of a survival-theoretic interpretation of Mamba hidden states, where regime instability is mapped to hazard and hidden-state energy to regime lifetime. This archive serves as a prior disclosure supporting a formal theoretical exposition hosted on DIO.

Fields of Study & Subjects

Neural Networks and Applications Probability and Statistical Research Machine Learning in Healthcare

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
15 January 2026