Deep learning has improved precipitation estimation and forecasting, but high predictive skill does not by itself ensure physically credible behavior, robustness under distribution shift, or reliable uncertainty. This critical narrative review examines physics-informed deep learning across quantitative precipitation es...
Hao Yang, Yan-Ni Wang, Min Chen et al.· Atmosphere· 0 citations
Accurate assimilation of satellite-derived precipitation data remains a critical challenge in regional numerical weather prediction (NWP), particularly for convective-scale rainfall. Conventional observation operators rely on radiative transfer models or simplified moist physics, introducing substantial uncertainty at...
Yang Huang, Yan-Song Bao, Fu Wang et al.· Remote Sensing· 0 citations
Method is presented, a classical density-matrix representation learning framework for hyperspectral images that supports constrained matrix-state learning as a practical alternative to vector-only hyperspectral classification without requiring quantum hardware.
Weijia Cao, Xiaofei Yang, Fu Wang et al.· arXiv.org· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.