Representation learning with contrastive predictive coding A Oord, Y Li, O Vinyals arXiv preprint arXiv:1807.03748, 2018 | 9527 | 2018 |
WaveNet: A Generative Model for Raw Audio A van den Oord, S Dieleman, H Zen, K Simonyan, O Vinyals, A Graves, ... arXiv preprint arXiv:1609.03499, 2016 | 8979* | 2016 |
Neural discrete representation learning A Van Den Oord, O Vinyals Advances in neural information processing systems 30, 2017 | 4355 | 2017 |
Pixel recurrent neural networks A Van Den Oord, N Kalchbrenner, K Kavukcuoglu International conference on machine learning, 1747-1756, 2016 | 2841 | 2016 |
Conditional image generation with pixelcnn decoders A Van den Oord, N Kalchbrenner, L Espeholt, O Vinyals, A Graves Advances in neural information processing systems 29, 2016 | 2839 | 2016 |
Generating diverse high-fidelity images with vq-vae-2 A Razavi, A Van den Oord, O Vinyals Advances in neural information processing systems 32, 2019 | 1766 | 2019 |
Deep content-based music recommendation A Van den Oord, S Dieleman, B Schrauwen Advances in neural information processing systems 26, 2013 | 1653 | 2013 |
Data-efficient image recognition with contrastive predictive coding OJ Hénaff, A Srinivas, J De Fauw, A Razavi, C Doersch, ASM Eslami, ... International Conference on Machine Learning, 4182-4192, 2020 | 1591 | 2020 |
A note on the evaluation of generative models L Theis, A Oord, M Bethge arXiv preprint arXiv:1511.01844, 2015 | 1308 | 2015 |
Efficient neural audio synthesis N Kalchbrenner, E Elsen, K Simonyan, S Noury, N Casagrande, ... International Conference on Machine Learning, 2410-2419, 2018 | 1012 | 2018 |
Parallel wavenet: Fast high-fidelity speech synthesis A Oord, Y Li, I Babuschkin, K Simonyan, O Vinyals, K Kavukcuoglu, ... International conference on machine learning, 3918-3926, 2018 | 989 | 2018 |
On variational bounds of mutual information B Poole, S Ozair, A Van Den Oord, A Alemi, G Tucker International Conference on Machine Learning, 5171-5180, 2019 | 857 | 2019 |
Count-based exploration with neural density models G Ostrovski, MG Bellemare, A Oord, R Munos International conference on machine learning, 2721-2730, 2017 | 730 | 2017 |
Neural machine translation in linear time N Kalchbrenner arXiv preprint arXiv:1610.10099, 2016 | 703 | 2016 |
Adversarial risk and the dangers of evaluating against weak attacks J Uesato, B O’donoghue, P Kohli, A Oord International conference on machine learning, 5025-5034, 2018 | 664 | 2018 |
Video pixel networks N Kalchbrenner, A Oord, K Simonyan, I Danihelka, O Vinyals, A Graves, ... International Conference on Machine Learning, 1771-1779, 2017 | 493 | 2017 |
Unsupervised speech representation learning using wavenet autoencoders J Chorowski, RJ Weiss, S Bengio, A Van Den Oord IEEE/ACM transactions on audio, speech, and language processing 27 (12 …, 2019 | 395 | 2019 |
Are we done with imagenet? L Beyer, OJ Hénaff, A Kolesnikov, X Zhai, A Oord arXiv preprint arXiv:2006.07159, 2020 | 385 | 2020 |
Beyond temporal pooling: Recurrence and temporal convolutions for gesture recognition in video L Pigou, A Van Den Oord, S Dieleman, M Van Herreweghe, J Dambre International Journal of Computer Vision 126, 430-439, 2018 | 340 | 2018 |
Parallel multiscale autoregressive density estimation S Reed, A Oord, N Kalchbrenner, SG Colmenarejo, Z Wang, Y Chen, ... International conference on machine learning, 2912-2921, 2017 | 239 | 2017 |