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20112025
most citedDistilling the Knowledge in a Neural Network

14.1k citations · 89.2k across the 108 of their papers we have counts for

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Showing 2016Show all

14 papers · 1 filter

cs.CV2016★ 615 cited

Lip Reading Sentences in the Wild

Joon Son Chung, Andrew Senior, Oriol Vinyals +1

The goal of this work is to recognise phrases and sentences being spoken by a talking face, with or without the audio. Unlike previous works that have focussed on recognising a lim…

cs.LG2016★ 1.1k cited

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…

cs.CL2016★ 5.7k cited

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…

cs.CV2016★ 21 cited

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…

cs.LG2016★ 93 cited

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…

cs.CV2016★ 922 cited

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…