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

1 Jun 2020Jie SunAbd AlRahman AlMomaniErik Bollt

Boolean functions and networks are commonly used in the modeling and analysis of complex biological systems, and this paradigm is highly relevant in other important areas in data science and decision making, such as in the medical field and in the finance industry. Automated learning of a Boolean network and Boolean functions, from data, is a challenging task due in part to the large number of unknowns (including both the structure of the network and the functions) to be estimated, for which a brute force approach would be exponentially complex... (read more)

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