BioinformaticsNature Computational SciencePeer-reviewed
A generalized and versatile framework to train and evaluate autoencoders for biological representation learning and beyond: AUTOENCODIX
Maximilian Josef Joas, Neringa Jurenaite, Dušan Praščević…·Jan Ewald
AUTOENCODIX provides a standardized framework for training and evaluating autoencoders, demonstrating its utility across multi-modal biological data and offering insights into representation learning trade-offs.
3 citations