Gated Recurrent Unit

A type of recurrent neural network architecture that uses gating mechanisms to control how much past information is retained or discarded at each step. GRUs are simpler than long short-term memorys but achieve comparable performance on many tasks, and were widely used for sequence modeling before transformers became the dominant architecture.
See also: long short-term memory, recurrent neural network, transformer.