Measuring dependence powerfully and equitably

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Measuring dependence powerfully and equitably

9 May 2015

Yakir A. Reshef

David N. Reshef

Pardis C Sabeti

Michael Mitzenmacher

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Papers citing "Measuring dependence powerfully and equitably"

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Title
Visual Analytics of Multivariate Networks with Representation Learning and Composite Variable Construction Hsiao-Ying Lu Takanori Fujiwara Ming-Yi Chang Yang-chih Fu Anders Ynnerman Kwan-Liu Ma CML 76 3 0 16 Mar 2023
Augmenting data-driven models for energy systems through feature engineering: A Python framework for feature engineering Sandra Wilfling 26 1 0 04 Jan 2023
Measuring Association on Topological Spaces Using Kernels and Geometric Graphs Nabarun Deb Promit Ghosal B. Sen 516 50 0 05 Oct 2020
A Visual Analytics System for Multi-model Comparison on Clinical Data Predictions Yiran Li Takanori Fujiwara Y. Choi Katherine K. Kim K. Ma OOD 121 27 0 18 Feb 2020
A new coefficient of correlation S. Chatterjee 120 259 0 23 Sep 2019
Multivariate Rank-based Distribution-free Nonparametric Testing using Measure Transportation Nabarun Deb B. Sen 131 134 0 18 Sep 2019
The Hellinger Correlation G. Geenens P. Lafaye De Micheaux 108 32 0 24 Oct 2018
Symmetric Rank Covariances: a Generalised Framework for Nonparametric Measures of Dependence Luca Weihs Mathias Drton N. Meinshausen 85 63 0 18 Aug 2017
Optimal Copula Transport for Clustering Multivariate Time Series Gautier Marti Frank Nielsen Philippe Donnat OT AI4TS 150 8 0 27 Sep 2015
An Empirical Study of Leading Measures of Dependence David N. Reshef Yakir A. Reshef Pardis C Sabeti Michael Mitzenmacher 95 18 0 09 May 2015
Equitability, interval estimation, and statistical power Yakir A. Reshef David N. Reshef Pardis C Sabeti Michael Mitzenmacher 84 11 0 09 May 2015