ABSTRACT: We define a new class of "implicit" deep learning prediction rules that generalize the recursive rules of feedforward neural networks. These models are based on the solution of a fixed-point equation involving a single vector of hidden features, which is thus only implicitly defined. The new framework greatly simplifies the notation of deep learning, and opens up many new possibilities,...