Deep Learning, Artificial Intelligence, Resnet, Image Classification, Residual Network.
members. (a): Deleting increasing numbers of residual modules, increases error smoothly. This implies residual networks behave like ensembles. (b): k randomly sampled pairs of building blocks with compatible dimensionality are swapped. As corruption increases, the error smoothly increases as well.