Viktor Stein

collaborators

5 papers

cs.LG2026

SympFormer: Accelerated attention blocks via Inertial Dynamics on Density Manifolds

Viktor Stein, Wuchen Li, Gabriele Steidl

Transformers owe much of their empirical success in natural language processing to the self-attention blocks. Recent perspectives interpret attention blocks as interacting particle…

math.AP2024

Wasserstein Gradient Flows of MMD Functionals with Distance Kernels under Sobolev Regularization

Richard Duong, Nicolaj Rux, Viktor Stein +1

We consider Wasserstein gradient flows of maximum mean discrepancy (MMD) functionals $MMD_{K}^{2} (\cdot, ν)$ for positive and negative distance kernels $K (x, y) := \pm ∣ x - y ∣$ and…

math.AP2024

Wasserstein Gradient Flows of MMD Functionals with Distance Kernel and Cauchy Problems on Quantile Functions

Richard Duong, Viktor Stein, Robert Beinert +2

We give a comprehensive description of Wasserstein gradient flows of maximum mean discrepancy (MMD) functionals $F_{ν} := MMD_{K}^{2} (\cdot, ν)$ towards given target measu…

math.OC2024

Interpolating between Optimal Transport and KL regularized Optimal Transport using Rényi Divergences

Jonas Bresch, Viktor Stein

Regularized optimal transport (OT) has received much attention in recent years starting from Cuturi's introduction of Kullback-Leibler (KL) divergence regularized OT. In this paper…

stat.ML2024

Wasserstein Gradient Flows for Moreau Envelopes of f-Divergences in Reproducing Kernel Hilbert Spaces

Viktor Stein, Sebastian Neumayer, Nicolaj Rux +1

Commonly used $f$ -divergences of measures, e.g., the Kullback-Leibler divergence, are subject to limitations regarding the support of the involved measures. A remedy is regularizin…