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Liang et al., 2017 - Google Patents

Interpretable structure-evolving LSTM

Liang et al., 2017

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Document ID
7396279849203119498
Author
Liang X
Lin L
Shen X
Feng J
Yan S
Xing E
Publication year
Publication venue
Proceedings of the IEEE conference on computer vision and pattern recognition

External Links

Snippet

This paper develops a general framework for learning interpretable data representation via Long Short-Term Memory (LSTM) recurrent neural networks over hierarchal graph structures. Instead of learning LSTM models over the pre-fixed structures, we propose to …
Continue reading at openaccess.thecvf.com (PDF) (other versions)

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