Author

O. Zahm

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Preprint Jul 2026

Gradient-free Riemannian Langevin Sampler

We address the problem of efficiently sampling multimodal probability distributions, where standard Markov Chain Monte Carlo methods often suffer from poor mixing and mode trapping. To mitigate these issues, we propose Gradient-free Riemannian Langevin Sampler (GRiLS), a novel proposal that improves exploration without...

R. Baptista, O. Zahm · 0 citations