Interpretable Deep Learning Methods for Multiview Learning

arXiv:2302.07930v2 Announce Type: replace
Abstract: Technological advances have enabled the generation of unique and complementary types of data or views (e.g. genomics, proteomics, metabolomics) and opened up a new era in multiview learning research with the potential to lead to new biomedical discoveries. We propose iDeepViewLearn (Interpretable Deep Learning Method for Multiview Learning) for learning nonlinear relationships in data from multiple views while achieving feature selection. iDeepViewLearn combines deep learning flexibility with the statistical benefits of data and knowledge-driven feature …

abstract advances arxiv biomedical cs.lg data deep learning discoveries genomics proteomics research stat.me stat.ml type types