Author

Krzysztof Choromanski

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Preprint Sep 2026

Unlocking Geodesic Gromov-Wasserstein Distances for 3D Modeling

\textit{Gromov-Wasserstein Distances} (GWDs) provide quantitative ways of comparing probabilistic distributions defined on different metric spaces by applying techniques from the optimal transport theory. As such, GWD can be potentially useful in a large variety of applications ranging from graph matching problems to 3...

Krzysztof Choromanski, Derek Long, Ananya Parashar et al. · 0 citations

#machine learning Preprint Sep 2026

Structure-Adaptive Tree Field Integrators

Some of the first results showing that efficient to compute and accurate relaxations of the geodesic Sinkhorn-based solutions of the Optimal Transport problem can be derived by applying fast TFI methods are provided.

Millend Roy, Soham Samal, Ivan Zelich et al. · 0 citations

#machine learning Jul 2026

ClockRoPE: Random Fourier Rotations for Temporal Routine Modeling

This work investigates the expressiveness of general query/key rotations and finds that any normalized continuous positive-definite attention modulation function can be approximated by random rotations induced by its own Fourier transform, which is term Random Fourier Rotations.

Yi-Wen Chen, Joshua Ainslie, Krzysztof Choromanski et al. · arXiv.org · 0 citations