(24) GRU & S2S：Learning Phrase Representations using RNN Encoder–Decoder for SMT
计划完成深度学习入门的126篇论文第二十四篇，蒙特利尔大学的Yoshua Bengio领导的第一篇使用S2S架构并应用在Statistical Machine Translation的论文。 ABSTRACT&INTRODUCTION 摘要 本文提出了一种新的神经网络模型RNN Encoder–Decoder，该模型由两个RNN组成。一个RNN将符号序列编码为定长向量表示，另外一个RNN将符号序列
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相关文章
- 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. 翻译：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. 论文笔记：GRU----RNN Encoder-Decoder
- 9. Seq2Seq系列（一）：RNN Encoder-Decoder
- 10. encoder-decoder