| Show, attend and tell: Neural image caption generation with visual attention K Xu, J Ba, R Kiros, K Cho, A Courville, R Salakhudinov, R Zemel, ... International conference on machine learning, 2048-2057, 2015 | 12360 | 2015 |
| Prototypical networks for few-shot learning J Snell, K Swersky, R Zemel Advances in neural information processing systems 30, 2017 | 8832 | 2017 |
| Siamese neural networks for one-shot image recognition G Koch, R Zemel, R Salakhutdinov ICML deep learning workshop 2 (1), 2015 | 5192 | 2015 |
| Fairness through awareness C Dwork, M Hardt, T Pitassi, O Reingold, R Zemel Proceedings of the 3rd innovations in theoretical computer science …, 2012 | 4106 | 2012 |
| Gated graph sequence neural networks Y Li, D Tarlow, M Brockschmidt, R Zemel arXiv preprint arXiv:1511.05493, 2015 | 3934 | 2015 |
| Advances in neural information processing systems H Lyu, N Sha, S Qin, M Yan, Y Xie, R Wang Advances in neural information processing systems 32, 2019 | 3701* | 2019 |
| Skip-thought vectors R Kiros, Y Zhu, RR Salakhutdinov, R Zemel, R Urtasun, A Torralba, ... Advances in neural information processing systems 28, 2015 | 3123 | 2015 |
| Aligning books and movies: Towards story-like visual explanations by watching movies and reading books Y Zhu, R Kiros, R Zemel, R Salakhutdinov, R Urtasun, A Torralba, S Fidler Proceedings of the IEEE international conference on computer vision, 19-27, 2015 | 3053 | 2015 |
| Learning fair representations R Zemel, Y Wu, K Swersky, T Pitassi, C Dwork International conference on machine learning, 325-333, 2013 | 2054 | 2013 |
| Understanding the effective receptive field in deep convolutional neural networks W Luo, Y Li, R Urtasun, R Zemel Advances in neural information processing systems 29, 2016 | 2004 | 2016 |
| Autoencoders, minimum description length and Helmholtz free energy GE Hinton, R Zemel Advances in neural information processing systems 6, 1993 | 1872 | 1993 |
| Shortcut learning in deep neural networks R Geirhos, JH Jacobsen, C Michaelis, R Zemel, W Brendel, M Bethge, ... Nature Machine Intelligence 2 (11), 665-673, 2020 | 1783 | 2020 |
| The helmholtz machine P Dayan, GE Hinton, RM Neal, RS Zemel Neural computation 7 (5), 889-904, 1995 | 1700 | 1995 |
| Unifying visual-semantic embeddings with multimodal neural language models R Kiros, R Salakhutdinov, RS Zemel arXiv preprint arXiv:1411.2539, 2014 | 1665 | 2014 |
| Meta-learning for semi-supervised few-shot classification M Ren, E Triantafillou, S Ravi, J Snell, K Swersky, JB Tenenbaum, ... arXiv preprint arXiv:1803.00676, 2018 | 1530 | 2018 |
| Multiscale conditional random fields for image labeling X He, RS Zemel, MA Carreira-Perpinán Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision …, 2004 | 1271 | 2004 |
| Generative moment matching networks Y Li, K Swersky, R Zemel International conference on machine learning, 1718-1727, 2015 | 1011 | 2015 |
| Neural relational inference for interacting systems T Kipf, E Fetaya, KC Wang, M Welling, R Zemel International conference on machine learning, 2688-2697, 2018 | 941 | 2018 |
| Information processing with population codes A Pouget, P Dayan, R Zemel Nature Reviews Neuroscience 1 (2), 125-132, 2000 | 923 | 2000 |
| Exploring models and data for image question answering M Ren, R Kiros, R Zemel Advances in neural information processing systems 28, 2015 | 884 | 2015 |
