Physics-Informed Deep Learning

Reconstructing three-dimensional density from surface data in the North Atlantic Sea through the PIO-Net model featured image
Subsurface Density Reconstruction

Reconstructing three-dimensional density from surface data in the North Atlantic Sea through the PIO-Net model

This study evaluates the applicability of the physics-informed operator network (PIO-Net) for reconstructing subsurface density anomalies (SDAs) based on sea surface density. …

avatar
陈元红
•
阅读更多
Physics-informed deep operator learning based on reduced-order modelling for retrieving the ocean interior density from the surface featured image
Subsurface Density Reconstruction

Physics-informed deep operator learning based on reduced-order modelling for retrieving the ocean interior density from the surface

Exploring methods to reconstruct the ocean interior from surface data is a crucial focus in the study of ocean processes and phenomena due to the shortage of subsurface and …

avatar
陈元红
•
阅读更多
Data driven three-dimensional temperature and salinity anomaly reconstruction of the northwest Pacific Ocean featured image
Subsurface Density Reconstruction

Data driven three-dimensional temperature and salinity anomaly reconstruction of the northwest Pacific Ocean

By virtue of the rapid development of ocean observation technologies, tens of petabytes of data archives have been recorded, among which, the largest portion are those derived from …

avatar
陈元红
•
阅读更多