3 papers
math.ST2026
Minkowski tensors for point clouds and voxelized data: robust, asymptotically unbiased estimators
Daniel Hug, Michael A. Klatt, Dominik Pabst
Minkowski tensors, also known as tensor valuations, provide robust -point information for a wide range of random spatial structures. Local estimators for point clouds, e.g., rep…
math.MG2026
Kubota-type formulas and supports of mixed measures
Daniel Hug, Fabian Mussnig, Jacopo Ulivelli
Kubota's integral formula expresses the intrinsic volumes of a convex body as averages over its projections onto linear subspaces. In this work, we introduce a new class of Kubota-…
math.MG2024
Strengthened inequalities for the mean width and the -norm of origin symmetric convex bodies
Károly J. Böröczky, Ferenc Fodor, Daniel Hug
Barthe, Schechtman and Schmuckenschläger proved that the cube maximizes the mean width of symmetric convex bodies whose John ellipsoid (maximal volume ellipsoid contained in the b…