24 citations · 89 across the 26 of their papers we have counts for
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cs.LG2019★ 15 cited
Variable Selection with Copula Entropy
Jian Ma
Variable selection is of significant importance for classification and regression tasks in machine learning and statistical applications where both predictability and explainabilit…
cs.LG2019★ 15 cited
Estimating Transfer Entropy via Copula Entropy
Jian Ma
Causal discovery is a fundamental problem in statistics and has wide applications in different fields. Transfer Entropy (TE) is a important notion defined for measuring causality,…
cs.LG2019★ 11 cited
Discovering Association with Copula Entropy
Jian Ma
Discovering associations is of central importance in scientific practices. Currently, most researches consider only linear association measured by correlation coefficient, which ha…