论文笔记：Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling
感想 最近深度学习面试的时候，有个面试官问了我LSTM，我一下子傻眼了，确实不怎么好懂，学LSTM已经有半年的时间了，但是对这个玩意儿却还不怎么明白，可能是没用过它的缘故吧，我找了一篇它和GRU比较的论文，这篇论文没有从理论上证明哪个模型的好坏，只是从实验，应用场景的角度发现GRU在一些场景比LSTM强，GRU是2014年提出的模型，可以说是一种LSTM的变体，使得计算和更新效率提高了，并且还取得
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相关文章
- 1. 论文笔记：An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling
- 2. Gated Recurrent Unit (GRU)
- 3. Document Modeling with Gated Recurrent Neural Network for Sentiment Classification 论文阅读笔记
- 4. 【论文阅读笔记】Document Modeling with Gated Recurrent Neural Network for Sentiment Classification
- 5. 【论文速读】Gated Feedback Recurrent Neural Network
- 6. Recurrent Neural Networks 简述
- 7. Sequence Models(Week1)---Recurrent Neural Networks
- 8. Gated Recurrent Unit（GRU）
- 9. A Critical Review of Recurrent Neural Networks for Sequence Learning
- 10. Supervised Sequence Labelling with Recurrent Neural Networks 笔记 -LSTM