Randomized Algorithms for Operator Approximations in Sobolev Spaces

Machine learning and artificial intelligence has been successful in the approximation and prediction of complex physical phenomena. A key aspect is the development of models capable of capturing dependencies on input parameters, domain configurations, boundary conditions, initial states, and spacetime coordinates within one neural network. One…