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

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

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

Bundle Adjustment for Close-Range Photogrammetry

Scikit-learn compatible estimation of general graphical models

World beating online covariance and portfolio construction.

Finding out the most relevant features for pricing of a house

This repository is a comprehensive archive of projects and assignments undertaken for the Pattern Recognition course (TIP8311) at the Federal University of Ceará as part of my Master's curriculum.

Implimentation of kalman filter for a vehicle with unknown location, noisy measurements using python

A Python class to read the records and attributes from the background error covariance matrices compatible with the Gridpoint Statistical Interpolation (in the .gcv file format)

R package for statistics of eigenvalue dispersion indices

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

[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)

Construction of PCA class from scratch and 3 implementations of PCA.

R Package That Can Simultaneously Perform Factor Analysis And Cluster Analysis Of Count Data Via Parsimonious Finite Mixtures of Multivariate Poisson-Log Normal Factor Analyzers. This Model Permits For Parsimonious Covariance Structures And Dimension Reduction, Thus Reducing The Number Of Free Parameters To Be Calculated.

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.

This repository is a series of notebooks that show analysis and modeling of the Breast Cancer data from Kaggle.

Deliverables relating to the Individual Assigned Practical Task (A Guide to Principal Component Analysis) University Unit

Mean and Covariance Matrix Estimation under Heavy Tails

Explore the cutting edge of NLP with this deep learning repository, featuring models for text classification, sentiment analysis, and more.