Learning to Bound: Monotonic, Calibrated Neural Upper Bounds for MPE Inference.

arXiv:2610.39305v1 Announce Type: cross Abstract: Probabilistic graphical models (PGMs) compactly encode structured joint distributions, but Most Probable Explanation (MPE), which finds the highest-probability assignment to unobserved variables, remains comput