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Richard Zemel
Richard Zemel
Professor of Computer Science, University of Toronto
Zweryfikowany adres z cs.toronto.edu - Strona główna
Tytuł
Cytowane przez
Cytowane przez
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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
90032015
Prototypical networks for few-shot learning
J Snell, K Swersky, R Zemel
Advances in neural information processing systems 30, 2017
41762017
Siamese neural networks for one-shot image recognition
G Koch, R Zemel, R Salakhutdinov
ICML deep learning workshop 2, 0, 2015
30992015
Skip-thought vectors
R Kiros, Y Zhu, RR Salakhutdinov, R Zemel, R Urtasun, A Torralba, ...
Advances in neural information processing systems 28, 2015
25322015
Gated graph sequence neural networks
Y Li, D Tarlow, M Brockschmidt, R Zemel
arXiv preprint arXiv:1511.05493, 2015
23202015
Fairness through awareness
C Dwork, M Hardt, T Pitassi, O Reingold, R Zemel
Proceedings of the 3rd innovations in theoretical computer science …, 2012
21732012
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
16072015
The helmholtz machine
P Dayan, GE Hinton, RM Neal, RS Zemel
Neural computation 7 (5), 889-904, 1995
14251995
Autoencoders, minimum description length and Helmholtz free energy
GE Hinton, R Zemel
Advances in neural information processing systems 6, 1993
13271993
Unifying visual-semantic embeddings with multimodal neural language models
R Kiros, R Salakhutdinov, RS Zemel
arXiv preprint arXiv:1411.2539, 2014
12712014
Learning fair representations
R Zemel, Y Wu, K Swersky, T Pitassi, C Dwork
International conference on machine learning, 325-333, 2013
12672013
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
12332004
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
10192016
Information processing with population codes
A Pouget, P Dayan, R Zemel
Nature Reviews Neuroscience 1 (2), 125-132, 2000
8312000
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
8012018
Generative moment matching networks
Y Li, K Swersky, R Zemel
International conference on machine learning, 1718-1727, 2015
7572015
Multimodal neural language models
R Kiros, R Salakhutdinov, R Zemel
International conference on machine learning, 595-603, 2014
7382014
Exploring models and data for image question answering
M Ren, R Kiros, R Zemel
Advances in neural information processing systems 28, 2015
6802015
Inference and computation with population codes
A Pouget, P Dayan, RS Zemel
Annual review of neuroscience 26 (1), 381-410, 2003
5482003
Probabilistic interpretation of population codes
RS Zemel, P Dayan, A Pouget
Neural computation 10 (2), 403-430, 1998
4861998
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