讀書筆記26：adding attentiveness to the neurons in recurrent neural networks
https://arxiv.org/pdf/1807.04445.pdf 摘要首先介紹RNN可以模擬複雜的序列信息的temporal dynamics，但是當前的RNN神經元的結構主要是控制當前信息和歷史信息的貢獻，但是沒有考慮探索input vector中不同元素的重要性（這個指的是某一個時刻的vector的不同dimension的重要性），因此本文提出了element-wise-attenti
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相關文章
- 1. Introduction to Recurrent Neural Networks
- 2. [ICLR19] ORDERED NEURONS: INTEGRATING TREE STRUCTURES INTO RECURRENT NEURAL NETWORKS
- 3. The Unreasonable Effectiveness of Recurrent Neural Networks
- 4. Recurrent Neural Networks Tutorial閱讀筆記
- 5. 【閱讀筆記】《ReNet: A Recurrent Neural Network Based Alternative to Convolutional Networks》
- 6. Multiresolution Recurrent Neural Networks: An Application to...
- 7. Towards End-to-end Text Spotting with Convolutional Recurrent Neural Networks閱讀筆記
- 8. 讀書筆記---Explain Images with Multimodal Recurrent Neural Networks
- 9. 讀書筆記10：Non-local Neural Networks
- 10. LSTM Recurrent Neural Networks for Short Text and Sentiment Classication文章閱讀筆記