GeoPhy: Differentiable Phylogenetic Inference via Geometric Gradients of Tree Topologies

Takahiro Mimori, Michiaki Hamada

Keywords: phylogenetic inference, variational inference, control variates, hyperbolic space

TL;DR: Novel differentiable phylogenetic inference approach with continuous topological distributions

Abstract: Phylogenetic inference, grounded in molecular evolution models, is essential for understanding evolutionary relationships in biological data. While Variational Bayesian methods offer scalable models for biological analysis, reliable inference for latent tree topology and branch lengths remains challenging due to the vast possibilities for topological candidates. In response, we introduce GeoPhy, a novel approach that employs a fully differentiable formulation of phylogenetic inference, representing topological distributions in continuous geometric spaces without limiting topological candidates. In experiments using real benchmark datasets, GeoPhy significantly outperformed other approximate Bayesian methods that considered whole topologies.

Submission Number: 61