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Marked Edge Walk: New MCMC Method for Sampling Graph Partitions
A new arXiv paper introduces the Marked Edge Walk, a Markov Chain Monte Carlo algorithm designed to sample graph partitions more effectively. The work targets redistricting analysis, where large ensembles of plans are generated by treating districts as graph partitions, and positions itself against existing methods such as Reversible Recombination. The abstract indicates the approach is intended to address limitations in current sampling techniques.