ITE can estimate entropy, mutual information, divergence, association measures, distribution kernels
|17 Jul 2014||Hugo Latapie||
Thank you for this well-documented comprehensive collection.
|8 Feb 2015||Zoltan Szabo||
ITE is capable of estimating many different variants of entropy, mutual information, divergence, association measures, cross quantities and kernels on distributions. Thanks to its highly modular design, ITE supports additionally (i) the combinations of the estimation techniques, (ii) the easy construction and embedding of novel information theoretical estimators, and (iii) their immediate application in information theoretical optimization problems.
For further details, see https://bitbucket.org/szzoli/ite/