Canonical Correlation Analysis Zoo: A collection of Regularized, Deep Learning based, Kernel, and Probabilistic methods in a scikit-learn style framework
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Updated
Apr 19, 2024 - Python
Canonical Correlation Analysis Zoo: A collection of Regularized, Deep Learning based, Kernel, and Probabilistic methods in a scikit-learn style framework
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.
Deep Canonical Correlation Analysis with Python
The code of the paper: M. Karami, D. Schuurmans, "Deep Probabilistic Canonical Correlation Analysis" AAAI 2021
An implementation of Deep Canonical Correlation Analysis (DCCA or Deep CCA) in Keras with tfv2 backend.
NeurIPS 2019: Deep RGB-D Canonical Correlation Analysis For Sparse Depth Completion
ISC method for M/EEG data
Deep Multiset Canonical Correlation Analysis - An extension of CCA to multiple datasets
Generalized Canonical Correlation Analysis - python 3 version
Time-dependent Canonical Correlation Analysis
Efficient sparse matrix implementation for various "Principal Component Analysis"
Assignment for Fall 2017 CS289: Machine Learning
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