An attention-augmented LSTM enhances the standard Long Short-Term Memory network by integrating an attention mechanism, allowing the model to selectively focus on the most relevant parts of an input sequence at each time step. This improves its ability to capture long-range dependencies and interpret temporal data more effectively.
An attention-augmented LSTM is a type of neural network that processes sequences of data, like medical records or sentences, by combining a memory-like component with a 'focusing' mechanism. This allows it to pay more attention to the most important parts of the sequence, leading to better predictions and a clearer understanding of what the model is learning.
Attn-LSTM, LSTM with Attention
Was this definition helpful?