Michael M. Bronstein

Intrinsic Geometry Matching: learning observation-equivariant process geometry

Real data are often arbitrary, indirect observations of an unknown underlying process, and those observations can distort its geometry. Existing geometric methods equip data with the induced geometry of the ambient space, but this entangles the true geometry of the process with the distortion of the observation. To add...