Richard Zemel
Richard Zemel
Professor of Computer Science, University of Toronto
Verified email at cs.toronto.edu - Homepage
TitleCited byYear
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
33802015
Skip-thought vectors
R Kiros, Y Zhu, RR Salakhutdinov, R Zemel, R Urtasun, A Torralba, ...
Advances in neural information processing systems, 3294-3302, 2015
11062015
The helmholtz machine
P Dayan, GE Hinton, RM Neal, RS Zemel
Neural computation 7 (5), 889-904, 1995
10291995
Multiscale conditional random fields for image labeling
X He, RS Zemel, MÁ Carreira-Perpiñán
Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision …, 2004
10052004
Information processing with population codes
A Pouget, P Dayan, R Zemel
Nature Reviews Neuroscience 1 (2), 125, 2000
6792000
Autoencoders, minimum description length and Helmholtz free energy
GE Hinton, RS Zemel
Advances in neural information processing systems, 3-10, 1994
6261994
Unifying visual-semantic embeddings with multimodal neural language models
R Kiros, R Salakhutdinov, RS Zemel
arXiv preprint arXiv:1411.2539, 2014
6112014
Siamese neural networks for one-shot image recognition
G Koch, R Zemel, R Salakhutdinov
ICML deep learning workshop 2, 2015
5982015
Fairness through awareness
C Dwork, M Hardt, T Pitassi, O Reingold, R Zemel
Proceedings of the 3rd innovations in theoretical computer science …, 2012
5642012
Gated graph sequence neural networks
Y Li, D Tarlow, M Brockschmidt, R Zemel
arXiv preprint arXiv:1511.05493, 2015
4762015
Inference and computation with population codes
A Pouget, P Dayan, RS Zemel
Annual review of neuroscience 26 (1), 381-410, 2003
4742003
Prototypical networks for few-shot learning
J Snell, K Swersky, R Zemel
Advances in Neural Information Processing Systems, 4077-4087, 2017
4432017
Probabilistic interpretation of population codes
RS Zemel, P Dayan, A Pouget
Neural computation 10 (2), 403-430, 1998
4101998
Multimodal neural language models
R Kiros, R Salakhutdinov, R Zemel
International Conference on Machine Learning, 595-603, 2014
4022014
Exploring models and data for image question answering
M Ren, R Kiros, R Zemel
Advances in neural information processing systems, 2953-2961, 2015
3392015
Learning fair representations
R Zemel, Y Wu, K Swersky, T Pitassi, C Dwork
International Conference on Machine Learning, 325-333, 2013
3372013
Generative moment matching networks
Y Li, K Swersky, R Zemel
International Conference on Machine Learning, 1718-1727, 2015
3252015
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
2532015
Object-based attention and occlusion: evidence from normal participants and a computational model.
M Behrmann, RS Zemel, MC Mozer
Journal of Experimental Psychology: Human Perception and Performance 24 (4 …, 1998
2461998
Learning and incorporating top-down cues in image segmentation
X He, RS Zemel, D Ray
European conference on computer vision, 338-351, 2006
2262006
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