
Mathematics in Engineering, 2020, 2(1): 3454. doi: 10.3934/mine.2020003.
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Topological features determining the error in the inference of networks using transfer entropy
1 Department of Mathematical Sciences, New Jersey Institute of Technology, Newark, New Jersey 07102, USA
2 Department of Mechanical and Aerospace Engineering & Department of Biomedical Engineering, New York University, Tandon School of Engineering, Brooklyn, New York 11201, USA
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Keywords: boolean network; datadriven; discrete systems; information theory; Markov chain; perturbation theory; policy diffusion
Citation: Roy H. Goodman, Maurizio Porfiri. Topological features determining the error in the inference of networks using transfer entropy. Mathematics in Engineering, 2020, 2(1): 3454. doi: 10.3934/mine.2020003
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This article has been cited by:
 1. Leonardo Novelli, Fatihcan M. Atay, Jürgen Jost, Joseph T. Lizier, Deriving pairwise transfer entropy from network structure and motifs, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2020, 476, 2236, 20190779, 10.1098/rspa.2019.0779
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