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To Read

  • Online Learning: A Comprehensive Survey [arXiv]
  • Visual Interpretability for Deep Learning: a Survey [arXiv]
  • CNN Is All You Need [arXiv]
  • The Matrix Calculus You Need For Deep Learning [arXiv]
  • Neural Collaborative Filtering [arXiv]
  • DensePose: Dense Human Pose Estimation In The Wild [arXiv] [article]
  • Nested LSTMs [arXiv]
  • Generating Wikipedia by Summarizing Long Sequences [arXiv]
  • Fine-tuned Language Models for Text Classification [arXiv] [code]
  • Deep Learning: An Introduction for Applied Mathematicians [arXiv]
  • Hierarchical Representations for Efficient Architecture Search [arXiv]
  • DroNet: Learning to Fly by Driving [UZH docs] [article] [code]
  • Deep Learning: A Critical Appraisal [arXiv]
  • The NarrativeQA Reading Comprehension Challenge [arXiv] [dataset]
  • Mathematics of Deep Learning [arXiv]
  • State-of-the-art Speech Recognition With Sequence-to-Sequence Models [arXiv] [article]
  • Peephole: Predicting Network Performance Before Training [arXiv]
  • Deliberation Network: Pushing the frontiers of neural machine translation [Research at Microsoft] [article]
  • Deep Learning Scaling is Predictable, Empirically [arXiv] [article]
  • Distilling a Neural Network Into a Soft Decision Tree [arXiv]
  • Neural Text Generation: A Practical Guide [arXiv]
  • CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning [arXiv] [article]
  • Online Deep Learning: Learning Deep Neural Networks on the Fly [arXiv]
  • Don't Decay the Learning Rate, Increase the Batch Size [arXiv]
  • Dynamic Routing Between Capsules [arXiv]
  • A generative vision model that trains with high data efficiency and breaks text-based CAPTCHAs [Science] [article] [code]
  • Malware Detection by Eating a Whole EXE [arXiv] [article]
  • Mastering the game of Go without Human Knowledge [Nature] [article]
  • A systematic study of the class imbalance problem in convolutional neural networks [arXiv]
  • Generalization in Deep Learning [arXiv]
  • Swish: a Self-Gated Activation Function [arXiv]
  • Generative Adversarial Networks: An Overview [arXiv]
  • The IIT Bombay English-Hindi Parallel Corpus [arXiv] [article]
  • Rainbow: Combining Improvements in Deep Reinforcement Learning [arXiv]
  • Neural Color Transfer between Images [arXiv]
  • StarSpace: Embed All The Things! [arXiv] [code]
  • Deep Reinforcement Learning that Matters [arXiv] [code]
  • WESPE: Weakly Supervised Photo Enhancer for Digital Cameras [arXiv] [article]
  • A Brief Introduction to Machine Learning for Engineers [arXiv]
  • A Deep Reinforcement Learning Chatbot [arXiv]
  • Efficient Methods and Hardware for Deep Learning (Thesis) [Stanford Digital Repository]
  • TensorFlow Agents: Efficient Batched Reinforcement Learning in TensorFlow [white paper] [code]
  • Deep Learning for Video Game Playing [arXiv]
  • Deep & Cross Network for Ad Click Predictions [arXiv]
  • Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms [arXiv] [code]
  • On the Effectiveness of Visible Watermarks [CVPR] [article]
  • On Ensuring that Intelligent Machines Are Well-Behaved [arXiv]
  • Training Deep AutoEncoders for Collaborative Filtering [arXiv] [code]
  • DARLA: Improving Zero-Shot Transfer in Reinforcement Learning [arXiv]
  • Eyemotion: Classifying facial expressions in VR using eye-tracking cameras [arXiv] [article]
  • Optimizing the Latent Space of Generative Networks [arXiv]
  • Learning Transferable Architectures for Scalable Image Recognition [arXiv]
  • Automatic Recognition of Deceptive Facial Expressions of Emotion [arXiv]
  • Revisiting Unreasonable Effectiveness of Data in Deep Learning Era [arXiv] [article]
  • Do GANs actually learn the distribution? An empirical study [arXiv]
  • Deep Interest Network for Click-Through Rate Prediction [arXiv]
  • One Model To Learn Them All [arXiv] [code] [article]
  • Deal or No Deal? End-to-End Learning for Negotiation Dialogues [S3AWS] [code] [article]
  • Attention Is All You Need [arXiv] [code] [article]
  • Sobolev Training for Neural Networks [arXiv]
  • Forward Thinking: Building and Training Neural Networks One Layer at a Time [arXiv]
  • Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour [arXiv]
  • pix2code: Generating Code from a Graphical User Interface Screenshot [arXiv] [article] [code]
  • Thinking Fast and Slow with Deep Learning and Tree Search [arXiv]
  • Look, Listen and Learn [arXiv]
  • Real-Time Adaptive Image Compression [arXiv]
  • Learning to Skim Text [arXiv]
  • Get To The Point: Summarization with Pointer-Generator Networks [arXiv] [code] [article]
  • DSLR-Quality Photos on Mobile Devices with Deep Convolutional Networks [arXiv] [article] [code]
  • Best Practices for Applying Deep Learning to Novel Applications [arXiv]
  • Controllable Text Generation [arXiv]
  • Evolving Deep Neural Networks [arXiv]
  • Opening the Black Box of Deep Neural Networks via Information [arXiv] [video]
  • Learning to Optimize Neural Nets [arXiv] [article]
  • The Shattered Gradients Problem: If resnets are the answer, then what is the question? [arXiv]
  • Deep Voice: Real-time Neural Text-to-Speech [arXiv]
  • Beating the World's Best at Super Smash Bros. with Deep Reinforcement Learning [arXiv]
  • The Game Imitation: Deep Supervised Convolutional Networks for Quick Video Game AI [arXiv]
  • All-but-the-Top: Simple and Effective Postprocessing for Word Representations [arXiv]
  • DyNet: The Dynamic Neural Network Toolkit [arXiv]
  • Quantum Machine Learning [arXiv]
  • Understanding deep learning requires rethinking generalization [arXiv]
  • Can Active Memory Replace Attention? [arXiv]
  • Xception: Deep Learning with Depthwise Separable Convolutions [arXiv]
  • Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation [arXiv]
  • Semi-Supervised Classification with Graph Convolutional Networks [arXiv]
  • Deep Neural Networks for YouTube Recommendations [paper]
  • Neural Machine Translation with Recurrent Attention Modeling [arXiv]
  • Recurrent Highway Networks [arXiv]
  • Bag of Tricks for Efficient Text Classification [arXiv]
  • Context-Dependent Word Representation for Neural Machine Translation [arXiv]
  • Concrete Problems in AI Safety [arXiv]
  • Smart Reply: Automated Response Suggestion for Email [arXiv]
  • Very Deep Convolutional Networks for Natural Language Processing [arXiv]
  • TensorFlow: A system for large-scale machine learning [arXiv]
  • Unsupervised Learning of Visual Representations by Solving Jigsaw Puzzles [arXiv]
  • A Persona-Based Neural Conversation Model [arXiv]
  • Natural Language Processing (almost) from Scratch [arXiv] - 2011