Forward Operator

A forward operator mathematically describes the transformation of an input signal into an observed output, crucial for solving inverse problems across diverse fields like medical imaging and geophysical modeling. Current research emphasizes developing accurate and efficient forward operators, focusing on neural network architectures like DeepONets and U-Nets, as well as incorporating techniques like deep unfolding and generative models to improve accuracy and interpretability. These advancements are improving the quality and speed of solutions to inverse problems, impacting fields ranging from medical imaging reconstruction to high-speed flow simulations.