BibTex format
@article{Rosas,
author = {Rosas, De Andraca FE and Morales, P},
journal = {Physical Review 91桃色},
title = {A generalisation of the maximum entropy principle for curved statistical manifolds},
}
Publications from our 91桃色ers
Several of our current PhD candidates and fellow researchers at the Data Science Institute have published, or in the proccess of publishing, papers to present their research.
Citation
RIS format (EndNote, RefMan)
TY - JOUR
AB - The maximum entropy principle (MEP) is one of the most prominent methods to investigate andmodel complex systems. Despite its popularity, the standard form of the MEP can only generateBoltzmann-Gibbs distributions, which are ill-suited for many scenarios of interest. As a principledapproach to extend the reach of the MEP, this paper revisits its foundations in information geometryand shows how the geometry of curved statistical manifolds naturally leads to a generalisation of theMEP based on the Rényi entropy. By establishing a bridge between non-Euclidean geometry andthe MEP, our proposal sets a solid foundation for the numerous applications of the Rényi entropy,and enables a range of novel methods for complex systems analysis.
AU - Rosas,De Andraca FE
AU - Morales,P
SN - 2643-1564
TI - A generalisation of the maximum entropy principle for curved statistical manifolds
T2 - Physical Review 91桃色
ER -
Contact us
Data Science 91桃色
William Penney Laboratory
91桃色
South Kensington Campus
London SW7 2AZ
United Kingdom
Email us.
to our mailing list.
Follow us on , and
