Hi,
I felt it might be good to make a list of all research papers that were referenced in this Sequence Models course by Prof. Ng. Please let me know if I have left out something.
Week 1
- Cho et al., 2014. On the properties of neural machine translation Encoder-decoder approaches
- Chung et al., 2014. Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modelling
- Hochreiter and Schmidhuber, 1997. Long short-term memory (I was unable to get link for free access)
Week 2
- van der Maaten and Hinton, 2008. Visualizing data using t-SNE
- Taigman et al., 2014. DeepFace: Closing the gap to human level performance
- Bengio et al., 2003. A neural probabilistic language model
- Mikolov et al., 2013. Efficient estimation of word representations in vector space
- Mikolov et al., 2013. Distributed representation of words and phrases and their compositionality
- Pennington et al., 2014. GloVe: Global vectors for word representation
- Bolukbasi et al., 2016. Man is to computer programmer as woman is to homemaker? Debiasing word embeddings
Week 3
- Sutskever et al., 2014. Sequence to sequence learning with neural networks
- Mao et al., 2014. Deep captioning with multimodal recurrent neural networks
- Vinyals et al., 2014. Show and tell: Neural image caption generator
- Karpathy and Fei-Fei, 2015. Deep visual-semantic alignment for generating image descriptions
- Papineni et al., 2002. Bleu: a method for automatic evaluation of machine translation
- Bandanau et al., 2014. Neural machine translation by jointly learning to align and translate
- Xu et al., 2015. Show, attend and tell: neural image caption generation with visual attention
- Graves et al., 2006. Connectionist temporal classification: labelling unsegmented sequence data with recurrent neural networks
Week 4
The reason I created this was because I was working on an NLP project and thought it would be nice if there was a single place where I could find all of the most important research papers.
Hope this helps,
Sushant Nair.