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20242026
most citedParallelly Sliced Optimal Transport on Spheres and on the Rotation Group

7 citations · 13 across the 8 of their papers we have counts for

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5 papers · 1 filter

cs.LG2024★ 1 cited

Optimizing Federated Learning by Entropy-Based Client Selection

Andreas Lutz, Gabriele Steidl, Karsten Müller +1

Although deep learning has revolutionized domains such as natural language processing and computer vision, its dependence on centralized datasets raises serious privacy concerns. F…

math.NA2024★ 1 cited

Slicing of Radial Functions: a Dimension Walk in the Fourier Space

Nicolaj Rux, Michael Quellmalz, Gabriele Steidl

Computations in high-dimensional spaces can often be realized only approximately, using a certain number of projections onto lower dimensional subspaces or sampling from distributi…

math.NA2024

Time-Harmonic Optical Flow with Applications in Elastography

Oleh Melnyk, Michael Quellmalz, Gabriele Steidl +3

In this paper, we propose mathematical models for reconstructing the optical flow in time-harmonic elastography. In this image acquisition technique, the object undergoes a special…

math.NA2024★ 7 cited

Parallelly Sliced Optimal Transport on Spheres and on the Rotation Group

Michael Quellmalz, Léo Buecher, Gabriele Steidl

Sliced optimal transport, which is basically a Radon transform followed by one-dimensional optimal transport, became popular in various applications due to its efficient computatio…

cs.LG2024★ 3 cited

Manifold GCN: Diffusion-based Convolutional Neural Network for Manifold-valued Graphs

Martin Hanik, Gabriele Steidl, Christoph von Tycowicz

We propose two graph neural network layers for graphs with features in a Riemannian manifold. First, based on a manifold-valued graph diffusion equation, we construct a diffusion l…