Accurate estimates of network parameters are essential for modeling, monitoring, and control in power distribution systems. In this paper, we develop a physics-informed graphical learning algorithm to estimate three-phase Our proposed uses only readily available smart meter data the series resistance reactance primary line segments. We first parametric physics-based model replace black-box deep...