Bidirectional Long Short-Term Memory (BI-LSTM) with Attention Mechanism

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By incorporating attention variants into an RNN (language models) opportunities are created for model introspection and analysis without sacrificing performance. Attention-equipped LSTM models have been used to improve performance on complex sequence modeling tasks. Attention provides a dynamic weighted average of values from different points in a calculation during the processing of a sequence to provide long term context for downstream discriminative or generative prediction. Recurrent Neural Network Attention Mechanisms for Interpretable System Log Anomaly Detection | Western Washington University and Pacific Northwest National Laboratory (PNNL