Estimation of Mutual Information: A Survey
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Title: Estimation of Mutual Information: A Survey

Section 1: Introduction
Description 1: Introduce Mutual Information (MI), its significance, and the aim of the paper, providing an overview of MI estimators and a summary of the paper's structure.

Section 2: Entropy
Description 2: Explain the concept of entropy, including its origin, definition, and various forms such as joint entropy, conditional entropy, and marginal entropy.

Section 3: Mutual Information
Description 3: Define Mutual Information, detail its properties and significance, and present different methods for estimating MI.

Section 4: Comparison Studies of Mutual Information Estimation
Description 4: Discuss various comparison studies that evaluate the performance of different MI estimators, including advantages and challenges of each method.

Section 5: Parametric vs. Nonparametric Methods
Description 5: Compare parametric and nonparametric estimation methods, detailing the strengths and weaknesses of each approach.

Section 6: Comparison of Estimators
Description 6: Provide detailed comparisons between specific MI estimation methods, including histogram vs KDE, B-spline vs KDE, KNN vs KDE, and others.

Section 7: Discussion and Conclusion
Description 7: Summarize the findings from the comparison studies, discussing the performance of different MI estimators and highlighting areas for future research.