I have been reading about LSTMs and GRUs, which are recurrent neural networks (RNNs). The difference between the two is the number and specific type of gates that they have. The GRU has an update gate, which has a similar role to the role of the input and forget gates in the LSTM.
Here's a diagram that illustrates both units (or RNNs).
With respect to the vanilla RNN, the LSTM has more "knobs" or parameters. So, why do we make use of the GRU, when we clearly have more control over the neural network through the LSTM model?
Here are two more specific questions.
When would one use Long Short-Term Memory (LSTM) over Gated Recurrent Units (GRU)?
What are the advantages/disadvantages of using LSTM over GRU?