13.4k citations · 28k across the 12 of their papers we have counts for
12 papers
Understanding deep learning requires rethinking generalization
Chiyuan Zhang, Samy Bengio, Moritz Hardt +2
Despite their massive size, successful deep artificial neural networks can exhibit a remarkably small difference between training and test performance. Conventional wisdom attribut…
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation
Yonghui Wu, Mike Schuster, Zhifeng Chen +28
Neural Machine Translation (NMT) is an end-to-end learning approach for automated translation, with the potential to overcome many of the weaknesses of conventional phrase-based tr…
Video Pixel Networks
Nal Kalchbrenner, Aaron van den Oord, Karen Simonyan +4
We propose a probabilistic video model, the Video Pixel Network (VPN), that estimates the discrete joint distribution of the raw pixel values in a video. The model and the neural a…
Connecting Generative Adversarial Networks and Actor-Critic Methods
David Pfau, Oriol Vinyals
Both generative adversarial networks (GAN) in unsupervised learning and actor-critic methods in reinforcement learning (RL) have gained a reputation for being difficult to optimize…
Show and Tell: Lessons learned from the 2015 MSCOCO Image Captioning Challenge
Oriol Vinyals, Alexander Toshev, Samy Bengio +1
Automatically describing the content of an image is a fundamental problem in artificial intelligence that connects computer vision and natural language processing. In this paper, w…
WaveNet: A Generative Model for Raw Audio
Aaron van den Oord, Sander Dieleman, Heiga Zen +6
This paper introduces WaveNet, a deep neural network for generating raw audio waveforms. The model is fully probabilistic and autoregressive, with the predictive distribution for e…