Authors

Gabriele Steidl

Publications 2

Preprint Open access

Neural Sampling with Reweighted Normalizing Flows via the Wasserstein--Fisher--Rao JKO Scheme

Chenguang Duan, Johannes Hertrich, Gabriele Steidl · 2026

We propose a neural algorithm for sampling from distributions specified by unnormalized Boltzmann densities. Our approach is based on the Jordan--Kinderlehrer--Otto scheme for the Kullback--Leibler divergence in the Wasserstein--Fisher--Rao geometry (WFR JKO scheme). Our contributions are twofold. First, we prove that, …

Preprint Open access

SOL: Measuring Gaps between Text Distributions by Double Sliced Wasserstein Metrics

Gregor Kornhardt, Moritz Piening, Jannis Chemseddine et al. · 2026

Evaluating text generation requires measuring how well the generated distribution matches the data distribution. For autoregressive models, this is done by the perplexity. Diffusion and flow-based language models can only provide a likelihood bound, whose tightness differs between model families. Sample-based substitut …

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