How to construct deep recurrent neural networks

Razvan Pascanu, Caglar Gulcehre, Kyunghyun Cho, Yoshua Bengio

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Original languageEnglish (US)
Title of host publicationProceedings of the Second International Conference on Learning Representations (ICLR 2014)
StatePublished - 2014

Cite this

Pascanu, R., Gulcehre, C., Cho, K., & Bengio, Y. (2014). How to construct deep recurrent neural networks. In Proceedings of the Second International Conference on Learning Representations (ICLR 2014)

How to construct deep recurrent neural networks. / Pascanu, Razvan; Gulcehre, Caglar; Cho, Kyunghyun; Bengio, Yoshua.

Proceedings of the Second International Conference on Learning Representations (ICLR 2014). 2014.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Pascanu, R, Gulcehre, C, Cho, K & Bengio, Y 2014, How to construct deep recurrent neural networks. in Proceedings of the Second International Conference on Learning Representations (ICLR 2014).
Pascanu R, Gulcehre C, Cho K, Bengio Y. How to construct deep recurrent neural networks. In Proceedings of the Second International Conference on Learning Representations (ICLR 2014). 2014
Pascanu, Razvan ; Gulcehre, Caglar ; Cho, Kyunghyun ; Bengio, Yoshua. / How to construct deep recurrent neural networks. Proceedings of the Second International Conference on Learning Representations (ICLR 2014). 2014.
@inproceedings{a81cdc63b81a42f5af92c81179c94532,
title = "How to construct deep recurrent neural networks",
author = "Razvan Pascanu and Caglar Gulcehre and Kyunghyun Cho and Yoshua Bengio",
year = "2014",
language = "English (US)",
booktitle = "Proceedings of the Second International Conference on Learning Representations (ICLR 2014)",

}

TY - GEN

T1 - How to construct deep recurrent neural networks

AU - Pascanu, Razvan

AU - Gulcehre, Caglar

AU - Cho, Kyunghyun

AU - Bengio, Yoshua

PY - 2014

Y1 - 2014

M3 - Conference contribution

BT - Proceedings of the Second International Conference on Learning Representations (ICLR 2014)

ER -