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Sponsored AI Networking Cookbook: Practical recipes for AI-assisted network automation and development AI Networking Cookbook: Practical recipes for AI-assisted network automation and development

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S. Götschel

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Open access Nov 2026

Comparing Transitional Markov Chain Monte Carlo and Metropolis–Hastings Sampling for Bayesian Bathymetry Reconstruction

Inference in Bayesian inverse problems frequently relies on sampling‐based methods for exploring the posterior distribution. In this paper, we compare two such methods for Bayesian bathymetry reconstruction from water‐surface elevation measurements: Metropolis–Hastings Markov chain Monte Carlo (MH‐MCMC) and transitio...

Lars Stietz, F. Bensel, S. Götschel et al. · 0 citations

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