論文筆記：Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling
感想 最近深度學習面試的時候，有個面試官問了我LSTM，我一下子傻眼了，確實不怎麼好懂，學LSTM已經有半年的時間了，但是對這個玩意兒卻還不怎麼明白，可能是沒用過它的緣故吧，我找了一篇它和GRU比較的論文，這篇論文沒有從理論上證明哪個模型的好壞，只是從實驗，應用場景的角度發現GRU在一些場景比LSTM強，GRU是2014年提出的模型，可以說是一種LSTM的變體，使得計算和更新效率提高了，並且還取得
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相關文章
- 1. 論文筆記：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 論文閱讀筆記
- 4. 【論文閱讀筆記】Document Modeling with Gated Recurrent Neural Network for Sentiment Classification
- 5. 【論文速讀】Gated Feedback Recurrent Neural Network
- 6. Recurrent Neural Networks 簡述
- 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 筆記 -LSTM