A new deep learning framework captures multi-scale spatio-temporal dependencies.
problem Designing and analyzing deep learning models for complex spatio-temporal analytics.
method Developed an IDRNN model with three modules for integrating and learning multi-scale spatio-temporal data.
result The IDRNN model outperforms classical and state-of-the-art models in capturing meaningful multi-scale spatio-temporal dependencies.