讀sequence to sequence 文章
文章中首先提到DNN，不能解決sequence2sequence的問題，因爲輸入和輸出固定的，但是對於翻譯等問題，序列的長度是不固定的，這篇文章主要是用了多層的LSTM，把輸入映射到一個固定的維度，然後再用另外一個LSTM，從這固定的向量去還原抽取目標序列。這裏測試場景是採用了英文到法文的翻譯，採用BLEU來度量效果。 1. 模型示意圖 輸入是ABC, 輸出是WXYZ 當輸出的序列
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相關文章
- 1. Attentive Sequence to Sequence Networks
- 2. sequence to sequence模型
- 3. Seq2Seq系列（二）:Sequence to Sequence
- 4. Convolutional Sequence to Sequence Learning 論文筆記
- 5. Sequence to Sequence模型理解
- 6. Write a Sequence to Sequence (seq2seq) Model
- 7. 論文閱讀：《AliMe Chat: A Sequence to Sequence and Rerank based Chatbot Engine》
- 8. 【論文閱讀】Sequence to Sequence Learning with Neural Network
- 9. 【論文閱讀】Incorporating copying mechanisim in sequence-to-sequence learning
- 10. 文獻閱讀筆記-MASS： Masked Sequence to Sequence Pre-training for Language Generation