An Experimental Comparison of Recurrent Neural Networks

Abstract

Many different discrete-time recurrent neural network architec(cid:173) tures have been proposed. However, there has been virtually no effort to compare these arch:tectures experimentally. In this paper we review and categorize many of these architectures and compare how they perform on various classes of simple problems including grammatical inference and nonlinear system identification.

Cite

Text

Horne and Giles. "An Experimental Comparison of Recurrent Neural Networks." Neural Information Processing Systems, 1994.

Markdown

[Horne and Giles. "An Experimental Comparison of Recurrent Neural Networks." Neural Information Processing Systems, 1994.](https://mlanthology.org/neurips/1994/horne1994neurips-experimental/)

BibTeX

@inproceedings{horne1994neurips-experimental,
  title     = {{An Experimental Comparison of Recurrent Neural Networks}},
  author    = {Horne, Bill G. and Giles, C. Lee},
  booktitle = {Neural Information Processing Systems},
  year      = {1994},
  pages     = {697-704},
  url       = {https://mlanthology.org/neurips/1994/horne1994neurips-experimental/}
}