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Papers discussed in the meetings of IITG.ai with summaries and resources.

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Paper-discussions

Papers discussed in the meetings of IITG.ai with summaries and resources.

Papers with summaries and resources

Papers with code and resources

  • An overview of gradient descent optimization algorithms. Sebastian Ruder. 2017. [Paper] [Slides] [Summary] [Code]
  • You Only Look Once: Unified, Real-Time Object Detection. Joseph Redmon, Santosh Divvala, Ross Girshick, Ali Farhadi. CVPR 2016. [Paper] [Slides] [Code]
  • A Style-Based Generator Architecture for Generative Adversarial Networks. CVPR 2019. [Paper] [Code]
  • Neural Turing Machines. Alex Graves, Greg Wayne, Ivo Danihelka. 2014. [Paper] [Code]
  • GloVe: Global Vectors for Word Representation. Jeffrey Pennington, Richard Socher, Christopher Manning. EMNLP 2014. [Slides] [Project Page] [Code]

Other papers with resources

  • Generative Adversarial Nets. Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, Yoshua Bengio. NIPS 2014. [Paper]
  • Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks. Alec Radford, Luke Metz, Soumith Chintala. ICLR 2016. [Paper]
  • Wasserstein GAN. Martin Arjovsky, Soumith Chintala, Léon Bottou. ICML 2017. [Paper]
  • Attention Is All You Need. Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, Illia Polosukhin. NIPS 2017. [Paper]
  • GloVe: Global Vectors for Word Representation. Jeffrey Pennington, Richard Socher, Christopher Manning. EMNLP 2014. [Project Page]