Does the universal approximation theorem for neural networks hold for any activation function (sigmoid, ReLU, Softmax, etc...) or is it limited to sigmoid functions? 

Update: As shimao points out in the comments, it doesn't hold for absolutely *any* function. So for which class of activation functions does it hold?