• Corpus ID: 35933354

T REE-STRUCTURED DECODING WITH DOUBLY-RECURRENT NEURAL NETWORKS

@inproceedings{AlvarezMelis2017TRD,
  title={T REE-STRUCTURED DECODING WITH DOUBLY-RECURRENT NEURAL NETWORKS},
  author={David Alvarez-Melis and T. Jaakkola},
  year={2017}
}
We propose a neural network architecture for generating tree-structured objects from encoded representations. The core of the method is a doubly recurrent neural network model comprised of separate width and depth recurrences that are combined inside each cell (node) to generate an output. The topology of the tree is modeled explicitly together with the content. That is, in response to an encoded vector representation, co-evolving recurrences are used to realize the associated tree and the… 

Ain't Nobody Got Time For Coding: Structure-Aware Program Synthesis From Natural Language

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