Dropout-LSTM+Noise(Bernoulli) (WT2)
Columbia UniversityNew York University (NYU)Princeton UniversityLanguage modeling
Dropout-LSTM+Noise(Bernoulli) (WT2) is a language modeling model from Columbia University,New York University (NYU),Princeton University released in 2018 with 51000000.0 parameters.
About Dropout-LSTM+Noise(Bernoulli) (WT2)
Recurrent neural networks (RNNs) are powerful models of sequential data. They have been successfully used in domains such as text and speech. However, RNNs are susceptible to overfitting; regularization is important. In this paper we develop Noisin,
Details
- Provider
- Columbia University,New York University (NYU),Princeton University
- Task
- Language modeling
- Parameters
- 51000000.0
- Released
- 2018-05-03
- Open weights
- No