A measure of mutual complete dependence

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Measuring Association on Topological Spaces Using Kernels and Geometric Graphs (2020, background): “Some multivariate measures of association satisfying (I)-(III) have been proposed in [92, 105, 16], following similar copula-based ideas as in [31]; however, to the best of our knowledge, none of these papers provide a consistent empirical estimate of their proposed measures of association.”
A Statistically and Numerically Efficient Independence Test Based on Random Projections and Distance Covariance (2017, background): “Test of independence is a fundamental problem in statistics, with many existing work including the maximal information coefficient (MIC) [1], the copula based measures [2,3], the kernel based criterion [4] and the distance correlation [5,6], which motivated our current work.”
On the exact region determined by Kendall's τ and Spearman's ρ (2015, unknown): “Some notions quantifying dependence of two-dimensional random variables which, contrary to Schweizer and Wolff’s σ (see [15]) are not based on d∞ have been studied in [18, 19].”
Copula-Based Measures of Multivariate Association (2010, background): “We further do not address measures of complete or functional dependence (see [50, 62, 68, 101]).”