Bo Li

Topology-modulated end-to-end graph learning for spatiotemporal state inference of urban drainage systems under sparse monitoring.

Reliable perception of urban drainage systems is essential for understanding the dynamic behaviour and managing water-environment risks. Yet structural and hydraulic complexity and sparse sensor deployment constrain the characterisation of evolving operational states. Here, we propose an end-to-end graph learning frame...