What is the new development in the LSTM model that also combines layers with LSTM?
LSTM architecture still has the same three gates Input, forget, Output Gates nothing changes and you can add more than one layer with multiple nodes. or you can combine more than one model to be like Stacked LSTM, Bidirectional LSTM, CNN LSTM
Long short-term memory (LSTM) is an artificial recurrent neural network (RNN) architecture used in the field of deep learning. ... LSTM networks are well-suited to classifying, processing and making predictions based on time series data, since there can be lags of unknown duration between important events in a time series.
Long short-term memory (LSTM) is an artificial recurrent neural network (RNN) architecture used in the field of deep learning. ... LSTM networks are well-suited to classifying, processing and making predictions based on time series data, since there can be lags of unknown duration between important events in a time series.
There are different LSTM networks. You check this interesting paper.
- Yu, Y., Si, X., Hu, C., & Zhang, J. (2019). A Review of Recurrent Neural Networks: LSTM Cells and Network Architectures. Neural Computation, 1–36. doi:10.1162/neco_a_01199
Personally, I used stacked LSTM in the below paper. You can check that too.
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