R. Manivannan

Positional Encoding Enhanced Graph Quantile Learning for Uncertainty-Aware Spatial Prediction

Spatial prediction is instrumental in environmental monitoring, urban studies, and geostatistics where accuracy and dependable uncertainty bounds are mandatory. This work introduces the Graph Quantile Neural Network (GQNN) with Positional Encoding (PE), which integrates graph-based spatial representation learning, the...