%0 Journal Article
%T Deriving pairwise transfer entropy from network structure and motifs
%A Fatihcan M. Atay
%A Joseph T. Lizier
%A Jrgen Jost
%A Leonardo Novelli
%J -
%D 2020
%R 10.1098/rspa.2019.0779
%X Transfer entropy (TE) is an established method for quantifying directed statistical dependencies in neuroimaging and complex systems datasets. The pairwise (or bivariate) TE from a source to a targ..
%U https://royalsocietypublishing.org/doi/10.1098/rspa.2019.0779