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Neural networks overcome dimensionality curse, revolutionize functional approximation.
A neural network has been developed to approximate complex functions, overcoming the curse of dimensionality. The network's approximation error is O(1/ √ m), where m is the network size. This breakthrough is achieved by defining a Barron space of functionals.