Topological Information Data Analysis

@article{Baudot2019TopologicalID,
  title={Topological Information Data Analysis},
  author={Pierre Baudot and M{\'o}nica Tapia and Daniel Bennequin and Jean-Marc Goaillard},
  journal={Entropy},
  year={2019},
  volume={21}
}
This paper presents methods that quantify the structure of statistical interactions within a given data set, and were applied in a previous article. It establishes new results on the k-multivariate mutual-information (Ik) inspired by the topological formulation of Information introduced in a serie of studies. In particular, we show that the vanishing of all Ik for 2≤k≤n of n random variables is equivalent to their statistical independence. Pursuing the work of Hu Kuo Ting and Te Sun Han, we… 
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26 Citations
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This goal is to provide the computational tools to explore neuroimaging data using topological data analysis and graph theory frameworks and to facilitate their accessibility, data visualisation, and comprehension for newcomers to the field.
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  • P. Baudot
  • Computer Science
    Physics of life reviews
  • 2019
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References

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