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20242026
most citedWasserstein Gradient Flows for Moreau Envelopes of f-Divergences in Reproducing Kernel Hilbert Spaces

1 citations · 2 across the 6 of their papers we have counts for

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math.NA2025

Numerical Methods for Kernel Slicing

Nicolaj Rux, Johannes Hertrich, Sebastian Neumayer

Kernels are key in machine learning for modeling interactions. Unfortunately, brute-force computation of the related kernel sums scales quadratically with the number of samples. Re…

stat.ML2025

Smoothed Distance Kernels for MMDs and Applications in Wasserstein Gradient Flows

Nicolaj Rux, Michael Quellmalz, Gabriele Steidl

Negative distance kernels were used in the definition of maximum mean discrepancies (MMDs) in statistics and lead to favorable numerical results in various ap…