From the docs:
HADES is a fast singularity detection algorithm. Singularities are points in data where the Manifold Hypothesis fails, such as cusps and self-intersections. HADES does not use topological methods, and instead works by (1) Locally applying dimensionality reduction and then (2) Performing a kernel goodness-of-fit test.