论文笔记-双向Attention：A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction
论文地址 GitHub代码地址 论文题目为《基于双阶段注意力机制的循环神经网络》,文章本质上还是基于Seq2Seq的模型，结合了注意力机制实现的时间序列的预测方法，文章的一大亮点是：不仅在解码器的输入阶段引入注意力机制，还在编码器阶段引入注意力机制，编码器的阶段的注意力机制实现了特征选取和把握时序依赖关系的作用。 分为两个阶段： 第一阶段：使用注意力机制从而能够自适应提取每个时刻的特征，这是本文的
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相关文章
- 1. A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction阅读笔记
- 2. [IJCAI 2017]A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction
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- 4. 论文笔记：Deep Convolutional Neural Network On Multichannel Time Series For Human Activity Recognition
- 5. 论文笔记：Autoregression Convolutional Neural Network for Asynchronous Time Series
- 6. Recurrent neural networks for multivariate time series with missing values文献阅读
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- 9. EA-LSTM: Evolutionary attention-based LSTM for time series prediction
- 10. 论文笔记：ReSeg: A Recurrent Neural Network-based Model for Semantic Segmentation