Data-Driven Learning of Boolean Networks and Functions by Optimal Causation Entropy Principle

Authors: Jie Sun, A. R. AlMomani, and Erik Bollt

Applies the Optimal Causation Entropy (OCE) principle to learning Boolean networks and their governing functions directly from data. The OCE framework identifies causal parents of each node and reconstructs Boolean update rules without requiring prior structural assumptions. This work received media coverage via EurekAlert.

Related Expertise

Causal Inference & Discovery (Pillar 1)