Sagnik Acharyya

MechGNN-Epi: Mechanistically Constrained Spatiotemporal Graph Learning for Regional Epidemic Forecasting

This work proposes MechGNN-Epi, a hybrid framework that couples a spatiotemporal graph encoder with a differentiable SIR update that yields epidemiologically constrained trajectories and produces region- and time-indexed parameter proxies that can be inspected as diagnostic signals, while not being guaranteed as causally identifiable mechanistic parameters.