Layer Normalization
At a glance
Layer normalization stabilizes training by rescaling signals within each example.
In one paragraph
Introduced a way to stabilize and speed up neural-network training by rescaling the signals within each layer for each individual example. Unlike batch normalization, it does not depend on groups of training examples and works naturally with networks that process sequences.
