The unprecedented amount of data generated from experiments, field observations, and large-scale numerical simulations at a wide range spatiotemporal scales has enabled the rapid advancement data-driven especially deep learning models in fluid mechanics. Although these methods are proven successful for many applications, there is grand challenge improving their generalizability. This particular...