Regime-adaptive partial differential equations for interpretable multi-ethnic urban modeling.

ABSTRACT: Machine learning models for societal applications often sacrifice interpretability for accuracy. We present the Multi-Ethnic Spatial Mixture of Experts (MESMoE), an interpretable framework integrating physics-informed modeling with specialized neural experts to predict urban population dynamics across ethnic groups. MESMoE addresses the challenge of capturing heterogeneous mechanisms that vary by ethnicity, spatial context, and temporal period through a learnable router that directs predictions to specialized experts for distinct demographic regimes (colonization, jump process, decline, and PDE-based diffusion). This approach achieves robust performance (R² values of 0.76-0.81 for 5-year forecasts, 0.71 for 10-year forecasts) while substantially outperforming seven baseline mode

SUBMITTER: Moghaddam SNM 

PROVIDER: S-EPMC12663275 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature