GraphIDyOM is a validated graph-native Python reimplementation of IDyOM that reproduces Lisp reference outputs with mean information-content differences below 0.003 bits and exposes predictive memories as graphs.
Predictive processes shape individual musical preferences.Proceedings of the National Academy of Sciences, 122(29):e2500494122, 2025
1 Pith paper cite this work, alongside 6 external citations. Polarity classification is still indexing.
1
Pith paper citing it
6
external citations · OpenAlex
fields
cs.SD 1years
2026 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
GraphIDyOM: A graph-native Python reimplementation of IDyOM for musical expectation modelling
GraphIDyOM is a validated graph-native Python reimplementation of IDyOM that reproduces Lisp reference outputs with mean information-content differences below 0.003 bits and exposes predictive memories as graphs.