Generalizing Metropolis-Hastings for DAG Sampling.

arXiv:2610.30291v1 Announce Type: cross Abstract: A fundamental challenge in Bayesian network structure learning lies in efficiently approximating the posterior distribution of directed acyclic graphs (DAGs). For large, high-dimensional datasets, the task rema