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

Ledoit-Wolf covariance matrix estimator of stock returns

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

Covariance Matrix Estimation via Factor Models

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

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

A Julia package for manipulating data in the Riemannian Manifold of Positive Definite Matrices

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

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

R package for adaptive correlation and covariance matrix shrinkage.

Estimation of the Covariance Matrix - linear and nonlinear shrinkage

Mean and Covariance Matrix Estimation under Heavy Tails

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

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

Skeleton-based method for activity recognition problem

Computation of Sparse Eigenvectors of a Matrix

An R package for testing high-dimensional covariance matrices

Bundle Adjustment for Close-Range Photogrammetry

[CVPR2023] The official repository for paper "Learning Partial Correlation based Deep Visual Representation for Image Classification" To appear in 2023 The IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR)

Jupyter notebooks with notes, code, and exercises from Linear Algebra: Theory, Intuition, Code by Mike X Cohen (2021).

Construct portfolios along mean-variance efficient frontier

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.

Generates R code for your lavaan models automatically, which helps with reproducible open science

The public repository for the code COFFE

COVMOS is an open-source Python library designed for rapidly simulating catalogues of cosmic objects in both real and redshift space.

Code for the paper E. Raninen and E. Ollila, "Bias Adjusted Sign Covariance Matrix," in IEEE Signal Processing Letters, vol. 29, pp. 339-343, 2022, doi: 10.1109/LSP.2021.3134940.

This project used Neural Networks and ARIMA to perform portfolio rebalancing. Their performance is measured using MSE and the more efficient algorithm is used to perform realtime portfolio rebalncing.