Convolutional Sequence to Sequence Learning學習心得
1 爲什麼使用CNN學習序列表示 和RNN相比，CNN產生的背景向量固定 並且通過stacking 可以使 contex size 更大，如下圖。 和RNN相比，CNN產生的背景向量固定 並且通過stacking 可以使 contex size 更大，如上圖。 Hierarchy representation 如圖1，只需要三次CNN operation ,而需要 7 次 rnn 才能覆蓋整個句子
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相關文章
- 1. Convolutional Sequence to Sequence Learning 論文筆記
- 2. Paper Reading - Convolutional Sequence to Sequence Learning ( CoRR 2017 ) ★
- 3. 【論文閱讀】Convolutional Sequence to Sequence Learning （未完待續）
- 4. 基於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學習筆記
- 10. Attentive Sequence to Sequence Networks