論文解讀：RECURRENT NEURAL NETWORK REGULARIZATION
論文地址：https://arxiv.org/pdf/1409.2329.pdf 一、RNN簡介 RNN（Recurrent Neural Network）是一類用於處理序列數據的神經網絡。神經網絡包含輸入層、隱層、輸出層，通過激活函數控制輸出，層與層之間通過權值連接。下圖一個標準的RNN結構圖，圖中每個箭頭代表做一次變換，也就是說箭頭連接帶有權值。左側是摺疊起來的樣子，右側是展開的樣子，左側中h
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相關文章
- 1. RNN(recurrent neural network regularization)
- 2. 【論文速讀】Gated Feedback Recurrent Neural Network
- 3. SESSION-BASED RECOMMENDATIONS WITH RECURRENT NEURAL NETWORKS論文解讀
- 4. CVPR 2017 On human motion prediction using recurrent neural networks 論文解讀
- 5. [論文解讀]A Quantitative Analysis Framework for Recurrent Neural Network
- 6. 論文解讀A Critical Review od Recurrent Neural Networks for Sequence Learning
- 7. Deep Learning 論文解讀——Session-based Recommendations with Recurrent Neural Networks
- 8. 【Recurrent Neural Network Regularization】讀後感（未編輯完畢）
- 9. 論文簡析之循環網絡中的正則化(Recurrent Neural Network With Regularization)
- 10. 論文筆記：Recurrent Neural Network Grammars