1. A computer-implemented method comprising: obtaining a plurality of training cases; and training a neural network having a plurality of layers on the plurality of training cases, each of the layers including one or more feature detectors, each of the feature detectors having a corresponding set of weights, and a subset of the feature detectors being associated with respective probabilities of being disabled during processing of each of the training cases, wherein training the neural network on the plurality of training cases comprises, for each of the training cases respectively: determining one or more feature detectors to disable during processing of the training case, comprising determining whether to disable each of the feature detectors in the subset based on the respective probability associated with the feature detector, disabling the one or more feature detectors in accordance with the determining, and processing the training case using the neural network with the one or more feature detectors disabled to generate a predicted output for the training case.