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Found 4 papers, 2 papers with code
A tutorial on multi-view autoencoders using the multi-view-AE library
Multi-view autoencoders have gained significant traction for their adaptability and versatility in modelling multi-modal data, demonstrating an ability to tailor their approach to suit the characteristics of the data at hand.
Unconstrained Stochastic CCA: Unifying Multiview and Self-Supervised Learning
The Canonical Correlation Analysis (CCA) family of methods is foundational in multiview learning.
Multi-modal Variational Autoencoders for normative modelling across multiple imaging modalities
We aim to develop a multi-modal normative modelling framework where abnormality is aggregated across variables of multiple modalities and is better able to detect deviations than uni-modal baselines.
A Generalized EigenGame with Extensions to Multiview Representation Learning
We demonstrate the effectiveness of our method for solving GEPs in the stochastic setting using canonical multiview datasets and demonstrate state-of-the-art performance for optimizing Deep CCA.
