(24) GRU & S2S：Learning Phrase Representations using RNN Encoder–Decoder for SMT
計劃完成深度學習入門的126篇論文第二十四篇，蒙特利爾大學的Yoshua Bengio領導的第一篇使用S2S架構並應用在Statistical Machine Translation的論文。 ABSTRACT&INTRODUCTION 摘要 本文提出了一種新的神經網絡模型RNN Encoder–Decoder，該模型由兩個RNN組成。一個RNN將符號序列編碼爲定長向量表示，另一個RNN將符號序列解
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- 1. (24) GRU & S2S：Learning Phrase Representations using RNN Encoder–Decoder for SMT
- 2. Learning Phrase Representations using RNN Encoder–Decoder for...
- 3. 2014-Learning Phrase Representations using RNN Encoder–Decoder
- 4. Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation
- 5. 翻譯：Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation
- 6. Paper：Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation
- 7. Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation之每日一篇
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相關文章
- 1. (24) GRU & S2S：Learning Phrase Representations using RNN Encoder–Decoder for SMT
- 2. Learning Phrase Representations using RNN Encoder–Decoder for...
- 3. 2014-Learning Phrase Representations using RNN Encoder–Decoder
- 4. Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation
- 5. 翻譯：Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation
- 6. Paper：Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation
- 7. Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation之每日一篇
- 8. 論文筆記：GRU----RNN Encoder-Decoder
- 9. Seq2Seq系列（一）：RNN Encoder-Decoder
- 10. encoder-decoder