Developing methods to accurately reconstruct spatial fields using data collected by sparse sensors has been a long-standing challenge in both physics and computer science. Ultimately, such methods could significantly aid the design, prediction, analysis and control of complex physical systems.
A deep learning technique for global field reconstruction with sparse sensors
