New paper on "Brain Age Prediction with MEG Brain Networks" accepted for Publication

Fully Hyperbolic Neural Networks -- A Novel Approach to Studying Aging Trajectories

Publication February 5, 2025

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We are excited to share our latest preprint, a collaboration with esteemed colleagues from MIT, UTHealth Houston, Johns Hopkins University, Complutense University of Madrid (Spain), and the University of Trento (Italy).

Title: Fully Hyperbolic Neural Networks – A Novel Approach to Studying Aging Trajectories
Authors: Hugo Ramirez, Davide Tabarelli, Arianna Brancaccio, Paolo Belardinelli, Elisabeth B. Marsh, Michael Funke, John C. Mosher, Fernando Maestu, Mengjia Xu*, and Dimitrios Pantazis*
Links: Download paper | GitHub Code | BibTex

People

Hugo Ramirez (Co-advised)
Master's Student (2022-2023)
EECS&Math (MIT)
Current position:

Software Engineer (Amazon Robotics, Greater Boston Area, MA)

Projects

Fully Hyperbolic Neural Networks - A Novel Approach to Studying Aging Trajectories

This study uses a Fully Hyperbolic Neural Network (FHNN) to embed MEG brain networks, uncovering age-related hierarchical changes and highlighting the superiority of hyperbolic features...