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, they do not reach their full potential. Recently, through the use of Riemannian geometry, we proposed a nonparametric framework for change-point detection in manifold-valued data streams [1]. We applied
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major challenge with dynamic structured data is finding representations that can effectively handle their underlying geometry, which is often defined by application-specific pseudo-distances. A common
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modeling and PDE) and our project would benefit greatly from the contribution in emerging fields — in their application to neuroscience —such as topology and geometry, or from an expertise in dynamical
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find a unified representation for the two modalities that allow an effective fusion. A large body of work simply projects LiDAR points to images using projective geometry (e.g.,[5, 6]) and uses the image