Topic: probabilistic network connectivity

Assessing the similarity of matrices is valuable for analyzing the extent to which data sets exhibit common features in tasks such as data clustering, dimensionality reduction, pattern recognition, group comparisons, and graph analysis. Methods proposed for comparing vectors, such as the cosine similarity, can be readily generalized to matrices. However, these approaches usually neglect the inherent two-dimensional structure of matrices. Existing methods that take this structure into account are only well-defined on square, symmetric, positive-definite matrices, limiting the range of applicabi