Estimating Copula Entropy (Mutual Information), Transfer Entropy (Conditional Mutual Information), and the statistics for multivariate normality test and two-sample test, and change point detection in Python

R package for estimating copula entropy (mutual information), transfer entropy (conditional mutual information), and the statistic for multivariate normality test and two-sample test

Python package for (conditional) independence testing and statistical functions related to causality.

A Python package implementing a variety of statistical methods that rely on kernels (e.g. HSIC for independence testing).

Algorithm-agnostic significance testing in supervised learning with multimodal data

Latent representation based Conditional Independence Test (LCIT) - ICDM 2022

Variable Selection with Knockoffs

Algorithm-agnostic significance testing in supervised learning with multimodal data

Code for the Paper "Evaluating Independence and Conditional Independence Measures"

The Adaptive Local Knockoff Filter

Reproducible R code for the master's thesis "Toward causality in mobile sensing for depression," using sparse functional data analysis (FDA) and conditional independence testing on the StudentLife datasets.

Detect new forecasting signals using time-varying nonlinear regression