A Python Package to Facilitate Statistical Research
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Updated
Aug 12, 2019 - Jupyter Notebook
A Python Package to Facilitate Statistical Research
Data imputation and feature reconstruction using deep learning
Code for the Paper "Evaluating Independence and Conditional Independence Measures"
Explore a newly developed methodology that could allow us to determine the pulsation and orbit periods of binary Cepheids without using any prior knowledge.
Python implementation of Distance Correlation, used to capture the linear and non-linear correlations between two continuous variables.
Raw files for a summary of various measures of dependency.
Code for the paper 'Variable Selection with Copula Entropy' published on Chinese Journal of Applied Probability and Statistics
energy package for R
Algorithms for quantifying associations, independence testing and causal inference from data.
Distance correlation and related E-statistics in Python
Disentagnled Graph Collaborative Filtering, SIGIR2020
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