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    Chapter and Conference Paper

    Equivariant Spherical Deconvolution: Learning Sparse Orientation Distribution Functions from Spherical Data

    We present a rotation-equivariant self-supervised learning framework for the sparse deconvolution of non-negative scalar fields on the unit sphere. Spherical signals with multiple peaks naturally arise in Dif...

    Axel Elaldi, Neel Dey, Heejong Kim… in Information Processing in Medical Imaging (2021)