Let's Read Deep Learning Paper!
- MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications (2017), Andrew G. Howard et al.
- Convolutional Sequence to Sequence Learning (2017), Jonas Gehring et al.
- Deep Photo Style Transfer (2017), F. Luan et al.
- CAN: Creative Adversarial Networks, Generating "Art" by Learning About Styles and Deviating from Style Norms
- Visualizing Data using t-SNE
- Attention Is All You Need
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
- Deep Complex Networks
- Inception-v4, inception-resnet and the impact of residual connections on learning (2016), C. Szegedy et al.
- GMM
- Visualizing and understanding convolutional networks (2014), M. Zeiler and R. Fergus
- Distilling the Knowledge in a Neural Network(2015)
- The Netflix Recommender System(2015)
- Wide&Deep Learning for Recommender Systems(2016)
- Playing Atari with Deep Reinforcement Learning
- Mastering the game of Go with deep neural networks and tree search
- Unsupervised representation learning with deep convolutional generative adversarial networks (2015), A. Radford et al.
- CFGAN: A Generic Collaborative Filtering Framework based on Generative Adversarial Networks
- GAIN: Missing Data Imputation using Generative Adversarial Nets
- Style Transfer from Non-Parallel Text by Cross-Alignment
- 2019-06-09
정현 Playing Atari with Deep Reinforcement Learning - Slide
경욱 Visualizing Data using t-SNE - Slide
- 2019-06-30
희선 Convolutional Neural Networks for Sentence Classification - Slide
연준 Gaussian Mixture Model - Slide
- 2019-07-07
인준 Latent Dirichlet Allocation - Slide
다빈 Attention Is All You Need - Slide
- 2019-07-21
성한 Distilling the knowledge in a Neural Network - Slide
지후 Generative Adversarial Nets - Slide
- 2018-08-11
정현 Alphagozero - Slide
- 2018-08-18
경욱 Photo Wake Up - Slide