AI RESEARCH
Diffusion Maps is not Dimensionality Reduction
arXiv CS.LG
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ArXi:2603.28037v1 Announce Type: new Diffusion maps (DMAP) are often used as a dimensionality-reduction tool, but precisely they provide a spectral representation of the intrinsic geometry rather than a complete charting method. To illustrate this distinction, we study a Swiss roll with known isometric coordinates and compare DMAP, Isomap, and UMAP across latent dimensions. For each representation, we fit an oracle affine readout to the ground-truth chart and measure reconstruction error.