Long short-term memory

A type of recurrent neural network (RNN) architecture designed to handle long-term dependencies in sequential data. Long short-term memory (LSTM) networks use a unique cell state and gating mechanism to control the flow of information, making them effective for tasks such as time series prediction, language modeling, and speech recognition. LSTMs are particularly beneficial for researchers and developers working on complex sequence-based data problems.

Long short-term memory was discovered on December 16th 2019 and it currently has a search volume of 135K with a growth of -14%.