Beyond Unimodal Bases: Pullback Geometry for Multimodal Data
Data-driven Riemannian geometry provides nonlinear interpolation and geometric representations of high-dimensional data. For these operations to be statistically meaningful, paths between observations should preferentially traverse high-likelihood regions. Existing scalable pullback constructions typically use a unimod...
Honglei Brinkmann, Lucas Ng, Georgios Batzolis et al.
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