Alexander Tolmachev

Towards Diverse and Comprehensive Benchmarks for Mutual Information Estimation

This work proposes two complementary families of tests: a copula-first family that systematically varies ground-truth mutual information, dimensionality, and marginal complexity using synthetic and flow-based transformations; and a marginals-first family that couples real-world image data with controlled dependency str...