GRU
Gated Recurrent Unit
A **Gated Recurrent Unit**, or **GRU**, is a type of recurrent neural network. It is similar to an [LSTM](https://paperswithcode.com/method/lstm), but only has two gates - a reset gate and an update gate - and notably lacks an output gate. Fewer parameters means GRUs are generally easier/faster to train than their LSTM counterparts.

Image Source: [here](https://www.google.com/url?sa=i&url=https%3A%2F%2Fcommons.wikimedia.org%2Fwiki%2FFile%3AGated_Recurrent_Unit%2C_type_1.svg&psig=AOvVaw3EmNX8QXC5hvyxeenmJIUn&ust=1590332062671000&source=images&cd=vfe&ved=0CA0QjhxqFwoTCMiev9-eyukCFQAAAAAdAAAAABAR)
Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation
https://paperswithcode.com/paper/learning-phrase-representations-using-rnn
Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation