Machine learning for multivariate data through the Riemannian geometry of positive definite matrices in Python

World beating online covariance and portfolio construction.

Scikit-learn compatible estimation of general graphical models

A MATLAB toolbox for classifier: Version 1.0.7

Fast, linear version of CorEx for covariance estimation, dimensionality reduction, and subspace clustering with very under-sampled, high-dimensional data

Ledoit-Wolf covariance matrix estimator of stock returns

Covariance Matrix Estimation via Factor Models

A 3D Scene Registration Method via Covariance Descriptors and an Evolutionary Stable Strategy Game Theory Solver

🪥 Unofficial re-implementation of Semi-orthogonal Embedding for Efficient Unsupervised Anomaly Segmentation

A library for machine learning and quantum programming based on pyRiemann and Qiskit projects

R package for adaptive correlation and covariance matrix shrinkage.

Performing the Financial Analysis on Historic Stock Market Data such as calculating various risks, returns,etc.

Mean and Covariance Matrix Estimation under Heavy Tails

Estimation of the Covariance Matrix - linear and nonlinear shrinkage

Covariance Estimation and Denoising for Cryo-EM Images (Covariance Wiener Filtering)

Companion repository of the "Near OOD detection for low-resolution radar micro-Doppler signatures" paper

Skeleton-based method for activity recognition problem

Computation of Sparse Eigenvectors of a Matrix

An R package for testing high-dimensional covariance matrices

Provides nonparametric Steinian shrinkage estimators of the covariance matrix that are suitable in high dimensional settings, that is when the number of variables is larger than the sample size.