Multiscale hyperbolic embedding reveals hierarchical structure in complex biological systems (opens in new tab)

The rapid expansion of biological and computational datasets demands scalable methods that support both visualization and quantitative interpretation. Hyperbolic embeddings are well-suited to represent hierarchical structure, but existing approaches are limited by fixed curvature assumptions or poor scalability to large datasets. We introduce MuH-MDS, a multiscale hyperbolic multidimensional scaling algorithm that employs an adiabatic optimization strategy: local positions are iteratively ref...