HOI: A Python toolbox for high-performance estimation of Higher-Order Interactions from multivariate data
Abstract
The HOI toolbox provides easy-to-use information theoretical metrics to estimate pairwise and higher-order information from multivariate data. The toolbox contains cutting-edge methods, along with core entropy and mutual information functions, which serve as building blocks for all metrics. In this way, HOI is accessible both to scientists with basic Python knowledge using pre-implemented functions and to experts who wish to develop new metrics on top of the core functions. Moreover, the toolbox supports computation on CPUs and GPUs. Finally, HOI provides tools for visualizing and presenting results to simplify the interpretation and analysis of the outputs.
Domains
Information Theory [cs.IT]| Origin | Publisher files allowed on an open archive |
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