Sequence to Sequence Learning with Neural Networks學習筆記
論文的主要創新點 提出了序列到序列的學習方法 提出的背景 DNN的限制： 輸入和輸出向量維度固定，實際上很多序列問題中的序列長度不是已知先驗 單個RNN 的限制： 輸入和輸出等長，且要一一對齊且對齊已知，無法應用到輸入輸出不等長且對應關係爲非montonic 解決方案 兩個RNN理論可行 一個負責將輸入充列map 爲固定大小的vector（背景向量，含有整個輸入句子的信息），另一個RNN將背景向列
相關文章
- 1. Sutskever2014_Sequence to Sequence Learning with Neural Networks
- 2. Paper：Sequence to Sequence Learning with Neural Networks
- 3. (25)[NIPS14] Sequence to Sequence Learning with Neural Networks
- 4. 《Sequence to Sequence Learning with Neural Networks》閱讀筆記
- 5. GRAPH2SEQ: GRAPH TO SEQUENCE LEARNING WITH ATTENTION-BASED NEURAL NETWORKS
- 6. 【論文閱讀】Sequence to Sequence Learning with Neural Networks
- 7. Sequence to Sequence Learning with Neural Networks 論文內容介紹
- 8. Sequence to Sequence Learning with Neural Networks論文翻譯
- 9. Sequence to Sequence Learning with Neural Networks，從RNN開始
- 10. 論文閱讀：Sequence to Sequence Learning with Neural Networks
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相關文章
- 1. Sutskever2014_Sequence to Sequence Learning with Neural Networks
- 2. Paper：Sequence to Sequence Learning with Neural Networks
- 3. (25)[NIPS14] Sequence to Sequence Learning with Neural Networks
- 4. 《Sequence to Sequence Learning with Neural Networks》閱讀筆記
- 5. GRAPH2SEQ: GRAPH TO SEQUENCE LEARNING WITH ATTENTION-BASED NEURAL NETWORKS
- 6. 【論文閱讀】Sequence to Sequence Learning with Neural Networks
- 7. Sequence to Sequence Learning with Neural Networks 論文內容介紹
- 8. Sequence to Sequence Learning with Neural Networks論文翻譯
- 9. Sequence to Sequence Learning with Neural Networks，從RNN開始
- 10. 論文閱讀：Sequence to Sequence Learning with Neural Networks