[论文阅读笔记] Massive Exploration of Neural Machine Translation Architectures
最近想要看看Attention的机制，然后被网上博客引到这个论文，想要了解一下NMT（Neural Machine Translation）的架构。这篇paper没有发表在会议上，出自Google Brain，并公开了seq2seq的NMT框架代码。个人觉得文中的结论不太可信，但是对于NMT的介绍还是足够清晰。这里记录一些文中有意思的点，以及一些笔者自己的思考，欢迎指教。 NMT框架 详见文中Se
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相关文章
- 1. 【论文】on the properties of neural machine translation :Encoder-decoder approaches 阅读笔记
- 2. Neural machine translation by jointly learning to align and translate论文阅读笔记
- 3. 论文 Non-Parametric Adaptation for Neural Machine Translation阅读笔记
- 4. 论文阅读笔记《Meta-Learning of Neural Architectures for Few-Shot Learning》
- 5. 论文阅读——Toward Making the Most of Context in Neural Machine Translation
- 6. Machine Learning & Deep Learning 论文阅读笔记
- 7. 文献阅读笔记：Phrase-Based & Neural Unsupervised Machine Translation
- 8. 【论文阅读】Neural Machine Translation By Jointly Learning To Align and Translate
- 9. 论文阅读：ByteNet, Neural Machine Translation in Linear Time
- 10. 论文阅读——Unsupervised Neural Machine Translation with Indirect Supervision