Fig. 1.

(a) The deep-NN architecture consists of a 3D stack of neural networks with identical architecture but different weights. When i and y vary, the outputs of the correspond to the predicted contact map at level k of the stack. A neural network purely spatial input features that depend only on i and j and are identical at all levels of the stack, and temporal input features associated with the contact probabilities predicted in the previous layer over a receptive field neighborhood of ij. (b) Input feature vector of each