Residual connection

Also: skip connection

Adding a sublayer's input to its output, so the sublayer only has to learn a correction rather than the whole mapping. Without it, gradients through a deep stack shrink to nothing and training stalls.

A definition is not an understanding. This is taught properly in Initialisation, normalisation and residuals, part of Neural networks.

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Terms from the same topic