If we want to learn about the hierarchical representation of sequential data, a stack of LSTM layers can be used. Each LSTM layer outputs a sequence of vectors rather than a single vector for each item of the sequence, which will be used as an input to a subsequent LSTM layer. This hierarchy of hidden layers enables a more complex representation of our sequential data. Stacked LSTM models can be used for modeling complex multivariate time series data.