14.5k citations · 48.8k across the 185 of their papers we have counts for
14 papers · 1 filter
Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling
Junyoung Chung, Caglar Gulcehre, KyungHyun Cho +1
In this paper we compare different types of recurrent units in recurrent neural networks (RNNs). Especially, we focus on more sophisticated units that implement a gating mechanism,…
End-to-end Continuous Speech Recognition using Attention-based Recurrent NN: First Results
Jan Chorowski, Dzmitry Bahdanau, Kyunghyun Cho +1
We replace the Hidden Markov Model (HMM) which is traditionally used in in continuous speech recognition with a bi-directional recurrent neural network encoder coupled to a recurre…
Embedding Word Similarity with Neural Machine Translation
Felix Hill, Kyunghyun Cho, Sebastien Jean +2
Neural language models learn word representations, or embeddings, that capture rich linguistic and conceptual information. Here we investigate the embeddings learned by neural mach…
On Using Very Large Target Vocabulary for Neural Machine Translation
Sébastien Jean, Kyunghyun Cho, Roland Memisevic +1
Neural machine translation, a recently proposed approach to machine translation based purely on neural networks, has shown promising results compared to the existing approaches suc…
Not All Neural Embeddings are Born Equal
Felix Hill, KyungHyun Cho, Sebastien Jean +2
Neural language models learn word representations that capture rich linguistic and conceptual information. Here we investigate the embeddings learned by neural machine translation…
On the Properties of Neural Machine Translation: Encoder-Decoder Approaches
Kyunghyun Cho, Bart van Merrienboer, Dzmitry Bahdanau +1
Neural machine translation is a relatively new approach to statistical machine translation based purely on neural networks. The neural machine translation models often consist of a…