An unsupervised pipeline that learns a density-aware Riemannian metric by mapping data to a uniform sphere with a normalizing flow and measuring distances through the flow's Jacobian.
Exact computation of a manifold metric, via lipschitz embeddings and shortest paths on a graph
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Learning Locally Adaptive Metrics that Enhance Structural Representation with $\texttt{LAMINAR}$
An unsupervised pipeline that learns a density-aware Riemannian metric by mapping data to a uniform sphere with a normalizing flow and measuring distances through the flow's Jacobian.