Bidirectional Long Short-Term Memory (BI-LSTM) with Attention Mechanism
Jump to navigation
Jump to search
Youtube search... ...Google search
- Recurrent Neural Network (RNN) Variants:
- Long Short-Term Memory (LSTM)
- Gated Recurrent Unit (GRU)
- Bidirectional Long Short-Term Memory (BI-LSTM)
- Bidirectional Long Short-Term Memory (BI-LSTM) with Attention Mechanism
- Average-Stochastic Gradient Descent (SGD) Weight-Dropped LSTM (AWD-LSTM)
- Hopfield Network (HN)
- Conversational AI ... ChatGPT | OpenAI ... Gemini | Google ... Claude | Anthropic ... Bing/Copilot | Microsoft ... Siri | Apple ... Meta ... Perplexity ... You ... phind ... Grok | xAI ... Groq ... Ernie | Baidu ... DeepSeek ... Alibaba
- Large Language Model (LLM) ... Multimodal ... Foundation Models (FM) ... Generative Pre-trained ... Transformer ... Attention ... GAN ... BERT
- Risk, Compliance and Regulation ... Ethics ... Privacy ... Law ... AI Governance ... AI Verification and Validation
- Cybersecurity ... OSINT ... Frameworks ... References ... Offense ... NIST ... DHS ... Screening ... Law Enforcement ... Government ... Defense ... Lifecycle Integration ... Products ... Evaluating
- Recurrent Neural Network Language Models for Open Vocabulary Event-Level Cyber Anomaly Detection | Pacific Northwest National Laboratory (PNNL)
- Deep Learning for Unsupervised Insider Threat Detection in Structured Cybersecurity Data Streams | Pacific Northwest National Laboratory (PNNL)
- SafeKit | Pacific Northwest National Laboratory (PNNL) - GitHub
- Attention-Based Bidirectional Long Short-Term Memory Networks for Relation Classification | Peng Zhou, Wei Shi, Jun Tian, Zhenyu Qi, Bingchen Li, Hongwei Hao, Bo Xu
- Taming Recurrent Neural Networks for Better Summarization | Abigail See
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
