Cristina Martin Linares - "AUTOENCODIX - a generalized and versatile framework to train and evaluate autoencoders for biological representation learning and beyond" (Joas et al.)
03 Feb 2026Overview
Paper Information
- Title: AUTOENCODIX: a generalized and versatile framework to train and evaluate autoencoders for biological representation learning and beyond
- Authors: Maximilian Josef Joas, Neringa Jurenaite, Dušan Praščević, Nico Scherf & Jan Ewald
- Journal: Nature Computational Science
- DOI & Link: https://www.nature.com/articles/s43588-025-00916-4
Slides
Below are the slides for this talk, embedded directly from Google Drive:
Slides
Contact
For questions or further discussion, please reach out to genomicdeeplearning@cs.jhu.edu