Deep learning and likelihood approaches for viral phylogeography converge on the same answers whether the inference model is right or wrong
A. Thompson, B. Liebeskind, E. J. Scully, M. Landis
This paper compares deep learning and likelihood methods for viral phylogeography, finding they produce similar results and robustness to model errors, with deep learning being significantly faster.
bioRxiv · Feb 8, 2023Evolutionary Biology