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

时间 2021-01-13

标签 Paper 繁體版

原文原文链接

本文的框架是： encode一个序列, decode一个tree structure, 并且在decode用了两个分开的recurrent neural network, 一个rnn 用于从model从根节点到当前节点i, 另一个rnn用于model 从最先开始生成的兄弟节点到目前节点i 。所以对应了paper的title doubly-recurrent Neural Networks, 具体看

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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

>>更多相关文章<<