It has long been known that patients with depression exhibit abnormal brain functional
connectivity patterns, that are often studied from a graph-theoretic perspective. However,
while certain simpler graph features have been examined, little has been done in the
direction of advanced feature learning methodologies such as network embeddings. Our
work aims to extend the understanding of importance of graph-based features for medical
applications by evaluating the recently proposed anonymous walk embeddings (AWE) in …