[ICLR2017]Tree-Structured Deconding with Doubly-Recurrent Neural Networks

時間 2021-01-13

標籤 Paper 简体版

原文原文鏈接

本文的框架是： encode一個序列, decode一個tree structure, 並且在decode用了兩個分開的recurrent neural network, 一個rnn 用於從model從根節點到當前節點i, 另一個rnn用於model 從最先開始生成的兄弟節點到目前節點i 。所以對應了paper的title doubly-recurrent Neural Networks, 具體看

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1. Few-shot Learning with Graph Neural Networks
2. Brain tumor segmentation with Deep Neural Networks
3. ImageNet Classification with Deep Convolutional Neural Networks
4. Convolutional Neural Networks with Alternately Updated Clique
5. Few-Shot Learning with Graph Neural Networks
6. Overlapping Community Detection with Graph Neural Networks
7. How to Implement Neural Networks with TensorFlow
8. Balanced Binary Neural Networks With Gated Residual
9. AlexNet：ImageNet Classification with Deep Convolutional Neural Networks
10. Sutskever2014_Sequence to Sequence Learning with Neural Networks

>>更多相關文章<<