Alejandro Aragón‐Zavala

Spatially validated physics-guided residual learning for indoor path loss prediction

Accurate indoor path loss prediction requires models that remain physically interpretable while capturing the structured variability introduced by walls, clutter, and non-line-of-sight propagation. This paper presents a physics-guided residual-learning framework for indoor path l...