Federico Larroca

A flexible hyperbolic optimization framework unlocks 46-74% loss reduction on hierarchical graphs by decoupling embedding and optimization curvatures.

Hyperbolic embeddings are powerful, but a fragmented ecosystem makes them hard to use—this framework finally puts them all in one place.

GNNs don't just detect time series anomalies better, they also offer a crucial interpretability boost for real-world diagnosis.