Deep Predictive Coding Networks (DPCN)

The overall goal of the dynamical system at any layer is to make the best prediction of the representation in the layer below using the top-down information from the layers above and the temporal information from the previous states.

Figure 1: Predictive Coding Network (PredNet). Left: Illustration of information flow within two layers. Each layer consists of representation neurons (Rl), which output a layer-specific prediction at each time step (Al), which is compared against a target (Al) (Bengio, 2014) to produce an error term (El), which is then propagated laterally and vertically in the network. Right: Module operations for case of video sequences.

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