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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…
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…