Canonical Correlation Analysis Zoo: A collection of Regularized, Deep Learning based, Kernel, and Probabilistic methods in a scikit-learn style framework

NeurIPS 2019: Deep RGB-D Canonical Correlation Analysis For Sparse Depth Completion

Deep Multiset Canonical Correlation Analysis - An extension of CCA to multiple datasets

A basic demonstration how to use Python, MNE, and PyTorch to analyze EEG signal.

MoMA: Modern Multivariate Analysis in R

Implementation of Fast ml-CCA from the ICCV-2015 work "Multi-Label Cross-Modal Retrieval"

Several examples of multivariate techniques implemented in R, Python, and SAS. Multivariate concrete dataset retrieved from https://archive.ics.uci.edu/ml/datasets/Concrete+Slump+Test. Credit to Professor I-Cheng Yeh.

Implementations of gradKCCA

Efficient sparse matrix implementation for various "Principal Component Analysis"

This repository includes useful MATLAB codes for the detection of SSVEP in EEG signals using spatial filters, frequency recognition algorithms, and machine-learning methods.

Data mining based approach to study the effect of caffeinated coffee on SSVEP brain signals. https://doi.org/10.1016/j.compbiomed.2019.103526

Case Study in ranking U.S. cities based on a single linear combination of rating variables. Dimensionality techniques used in the analysis are Principal Component Analysis (PCA), Factor Analysis (FA), Canonical Correlation Analysis (CCA)

Unsupervised Learning

Deep Canonical Correlation Analysis with Python

Time-dependent Canonical Correlation Analysis

TreeCorTreat

Sparse canonical correlation analysis

ISC method for M/EEG data

This repository contains materials associated to the course "Multivariate Analysis" taught at the Faculty of Mathematics and Statistics (FME), UPC under the MESIO-UPC-UB Interuniversity Program under the instructors "Ferran Revertar", "Miguel Salicru" and "Jan Graffelman"

Tensor-based Multiple Canonical Correlation Analysis