Machine learning for multivariate data through the Riemannian geometry of positive definite matrices in Python
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Updated
Sep 27, 2024 - Python
Machine learning for multivariate data through the Riemannian geometry of positive definite matrices in Python
A MATLAB toolbox for classifier: Version 1.0.7
Scikit-learn compatible estimation of general graphical models
World beating online covariance and portfolio construction.
A 3D Scene Registration Method via Covariance Descriptors and an Evolutionary Stable Strategy Game Theory Solver
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
Computation of Sparse Eigenvectors of a Matrix
A library for machine learning and quantum programming based on pyRiemann and Qiskit projects
Ledoit-Wolf covariance matrix estimator of stock returns
The public repository for the code COFFE
Performing the Financial Analysis on Historic Stock Market Data such as calculating various risks, returns,etc.
Estimation of the Covariance Matrix - linear and nonlinear shrinkage
Covariance Estimation and Denoising for Cryo-EM Images (Covariance Wiener Filtering)
Bundle Adjustment for Close-Range Photogrammetry
Construct portfolios along mean-variance efficient frontier
🪥 Unofficial re-implementation of Semi-orthogonal Embedding for Efficient Unsupervised Anomaly Segmentation
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.
Mean and Covariance Matrix Estimation under Heavy Tails
This repository contains data and code relative to the manuscript "A large covariance matrix estimator under intermediate spikiness regimes" by Matteo Farnè and Angela Montanari (https://arxiv.org/abs/1711.08950).
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