Spatio-Temporal Self-Supervised Learning for Traffic Flow Prediction: Enhancing Spatial and Temporal Heterogeneity Modeling

The author proposes a novel Spatio-Temporal Self-Supervised Learning (ST-SSL) framework to enhance traffic pattern representations by addressing spatial and temporal heterogeneity through adaptive self-supervised learning paradigms.