Operator learning

Operator learning refers to the process of learning operators in infinite-dimensional Hilbert or Banach spaces. Its goal is to construct mathematical models through data-driven methods that can accurately map inputs to outputs. This task has significant application value in solving complex function approximation problems, partial differential equation solutions, and signal processing, effectively enhancing computational efficiency and accuracy.