Paper Notes

Notes of papers related to deep learning, reinforcement learning, computer vision, natural language processing etc by Music Li.

Transformers

• Attention is all you need [NIPS'17]
• BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding [NAACL'19]

GANs

• StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks [arXiv'2017]
• Generating Images from Captions with Attention [ICLR'2016]
• Generating Text via Adversarial Training [Duke'2016]
• Wasserstein GAN [arXiv'2017]

Deep Reinforcement Learning

• Reinforcement learning with unsupervised auxiliary tasks [ICLR'2017]
• Playing Doom with SLAM-Augmented Deep Reinforcement Learning [arXiv'2016]
• Unifying Count-Based Exploration and Intrinsic Motivation [ICLR'2017]
• Value Iteration Networks [NIPS'16]

CNNs

• Conditional Image Generation with PixelCNN Decoders, [arXiv'2016]

RNNs

• Visualizing and Understanding Recurrent Networks [ICLR'2016]
• Pixel Recurrent Neural Networks [ICML'2016]

Question Answering

• SQuAD: 100,000+ Questions for Machine Comprehension of Text [EMNLP'2016]

Computer Vision

• DeViSE: A Deep Visual-Semantic Embedding Model [NIPS'2013]
• [Deep Convolutional Inverse Graphics Network] (https://github.com/pkumusic/Paper-Notes/blob/master/reviews/DC-IGN.md) [NIPS'2015]
• Baby Talk: Understanding and Generating Image Descriptions[CVPR'11]

Machine Translation

• Unsupervised Quality Estimation for Neural Machine Translation[20]