The integration of deep learning techniques and physics-driven designs is reforming the way we address inverse problems, in which accurate physical properties are extracted from complex observations.

Machine learning has greatly shaped the landscape of computational biology, with the integration of high-throughput data acquisition and burgeoning computational power leading to the creation of ...