Convolutional Sequence to Sequence Learning学习心得
1 为什么使用CNN学习序列表示 和RNN相比，CNN产生的背景向量固定 并且通过stacking 可以使 contex size 更大，如下图。 和RNN相比，CNN产生的背景向量固定 并且通过stacking 可以使 contex size 更大，如上图。 Hierarchy representation 如图1，只需要三次CNN operation ,而需要 7 次 rnn 才能覆盖整个句子
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相关文章
- 1. Convolutional Sequence to Sequence Learning 论文笔记
- 2. Paper Reading - Convolutional Sequence to Sequence Learning ( CoRR 2017 ) ★
- 3. 【论文阅读】Convolutional Sequence to Sequence Learning （未完待续）
- 4. 基于CNN的Seq2Seq模型-Convolutional Sequence to Sequence Learning
- 5. Incorporating Copying Mechanism in Sequence-to-Sequence Learning
- 6. (25)[NIPS14] Sequence to Sequence Learning with Neural Networks
- 7. [ACL2016] Incorporating Copying Mechanism in Sequence-to-Sequence Learning
- 8. Deep learning From Image to Sequence
- 9. Sequence to Sequence Learning with Neural Networks学习笔记
- 10. Attentive Sequence to Sequence Networks