Deeplearning.ai

Contains list of research papers on deep learning, cited in all deeplearning.ai courses.

SEQUENCE MODELS

• WEEK 1 : RECURRENT NEURAL NETWORKS

  1. The Unresonable Effectiveness of Recurrent Neural Networks -- Andrej Karpathy blogs
  2. Understanding LSTM Networks -- colah's blogs

• WEEK 2 : NATRUAL LANGUAGE PROCESSING AND WORD EMBEDDINGS

  1. Linguistic regularities in continous space word representation -- Microsoft Research Redmond, WA 98052
  2. Efficient Estimation of Word Representations in Vector Space -- Thomas Mikolov, Kai Chen, Greg Corrado, Jeffrey Dean
  3. GloVe: Global Vectors for Word Representation -- Jeffrey Pennington, Richard Socher, Christopher D. Manning
  4. Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings -- Tolga Bolukbasi, Kai-Wei Chang, James Zou, Venkatesh Saligrama, Adam Kalai

• WEEK 3 : SEQUENCE MODELS AND ATTENTION MECHANISM

  1. Neural Machine Translation by jointly learning to align and translate -- Dzmitry Bahdanau, KyungHyun Cho, Yoshua Bengio
  2. Show, Attend and Tell : Neural Image Caption Generation With Visual Attention -- Kelvin Xu, Jimmy Ba, Ryan Kiros, Kyunghyun Cho, Aaron Courville, Yoshua Benjio
  3. Connectionist Temporal Classification : Labelling Unsegmented Sequence Data with Recurrent Neural Networks -- Alex Graves, Santiago Fernandez, Faustino Gomez, Jurgen Schmidhuber