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A general method for the rapid recovery of plasma topology based on a neural network fit of the normalized magnetic flux is presented. We propose a general method for coordinate inversions that is based on a neural network fit of the normalized magnetic flux. The neural network provides a flexible and compact base for representing the plasma topology and allows the evaluation of spatial derivatives by analytic methods (as opposed to finite-difference methods), making it faster than other techniques. We present examples of this technique for both two-dimensional plasmas (tokamak D shaped, X point) and stellarators. © 1997 American Institute of Physics.