3 citations · 3 across the 2 of their papers we have counts for
6 papers
Stochastic Zeroth-Order Method for Computing Generalized Rayleigh Quotients
Jonas Bresch, Oleh Melnyk, Martin Schoen +1
The maximization of the (generalized) Rayleigh quotient is a central problem in numerical linear algebra. Conventional algorithms for its computation typically rely on matrix-adjoi…
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…
HOT-POT: Optimal Transport for Sparse Stereo Matching
Antonin Clerc, Michael Quellmalz, Moritz Piening +3
Stereo vision between images faces a range of challenges, including occlusions, motion, and camera distortions, across applications in autonomous driving, robotics, and face analys…
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…
Unsupervised Ground Metric Learning
Janis Auffenberg, Jonas Bresch, Oleh Melnyk +1
Data classification without access to labeled samples remains a challenging problem. It usually depends on an appropriately chosen distance between features, a topic addressed in m…
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…