####################################################
####################################################
This repository is concerned with providing python implementation for both novel and known algorithms for explainable multiview analysis using deep neural networks.
####################################################
####################################################
The developer notebook can be used to train the different models implemented. Currently, the data is just randomly generated to allow for exemplary demonstration on how to train and evaluate the models.
###########
###########
In case of questions, suggestions, problems etc. please send an email.
Tanuj Hasija: [email protected]
Maurice Kuschel: [email protected]
##############
##############
[1] S.Vieluf*, T.Hasija*, M.Kuschel, C.Reinsberger, and T.Loddenkemper, "Developing a deep canonical correlation-based technique for seizure prediction", Submitted, 2022.
[2] G.Andrew, R.Arora, J.Bilmes,and K.Livescu, "Deep canonical correlation analysis", International conference on machine learning, 2013.
[3] W.Wang, R.Arora, K.Livescu, and J.Bilmes. "On deep multi-view representation learning." International conference on machine learning, 2015.