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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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Hi James, I am trying to run the DCCA on my datasets X and Y both continuous numerical entries: Dataset X is the independent set having 2 features x1 and...

In their [paper from 2018](https://www.nature.com/articles/s41467-018-05317-y#Sec9), Xia et a. implemented a method to match canonical variates from resampled data sets to the original data set in order to be able to...

enhancement
help wanted
good first issue

I know this is easy to compute, but still nice to have out-of-the-box: Wouldn't it make sense to also add a `compute_covariance` method to `_CCA_Base`? Like such: ```python def explained_variance(X,y,X_weights,y_weights):...

enhancement
help wanted
good first issue

Hi, is it possible to run a subsection of these versions of CCA on GPU? If so, would you please write down a short example?

This is my first trial for this method (contributing to #124 ). The function is not working as expected yet, I think this is due to the way the correlation...

Hi, I run basic CCA on some dataset, it works well, but sometimes I get nans at the final columns of now of the transformed matrices, for example: ``` basic_cca...

Used to have these in the package and at some point removed them but now think they should be back

enhancement
good first issue

I have 3 data views and each have more than 10 variables. I use the MCCA function. I check the averaged pairwise correlation and explained covariance of constructed indices. The...

Sorry to disturb you again; but I am confused while coding the training loop by myself, is the loss calculated on the input data and not on the latent representation...

Everytime I try to run the Deep Multiset CCA, I come across this error "The algorithm failed to converge because the input matrix is ill-conditioned or has too many repeated...