A deep learning technique for global field reconstruction with sparse sensors

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.

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