Graham Taylor
Graham Taylor
University of Guelph and Vector Institute for Artificial Intelligence (Currently at Google Brain)
Verified email at - Homepage
TitleCited byYear
Deconvolutional networks
MD Zeiler, D Krishnan, GW Taylor, R Fergus
Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on …, 2010
Modeling human motion using binary latent variables
GW Taylor, GE Hinton, ST Roweis
Advances in neural information processing systems, 1345-1352, 2007
Adaptive deconvolutional networks for mid and high level feature learning.
MD Zeiler, GW Taylor, R Fergus
ICCV 1 (2), 6, 2011
Convolutional learning of spatio-temporal features
GW Taylor, R Fergus, Y LeCun, C Bregler
European conference on computer vision, 140-153, 2010
Factored conditional restricted Boltzmann machines for modeling motion style
GW Taylor, GE Hinton
Proceedings of the 26th annual international conference on machine learning …, 2009
The recurrent temporal restricted boltzmann machine
I Sutskever, GE Hinton, GW Taylor
Advances in neural information processing systems, 1601-1608, 2009
Multi-scale deep learning for gesture detection and localization
N Neverova, C Wolf, GW Taylor, F Nebout
European Conference on Computer Vision, 474-490, 2014
Dynamical binary latent variable models for 3d human pose tracking
GW Taylor, L Sigal, DJ Fleet, GE Hinton
2010 IEEE Computer Society Conference on Computer Vision and Pattern …, 2010
Moddrop: adaptive multi-modal gesture recognition
N Neverova, C Wolf, G Taylor, F Nebout
IEEE Transactions on Pattern Analysis and Machine Intelligence 38 (8), 1692-1706, 2016
Learning human pose estimation features with convolutional networks
A Jain, J Tompson, M Andriluka, GW Taylor, C Bregler
arXiv preprint arXiv:1312.7302, 2013
Two distributed-state models for generating high-dimensional time series
GW Taylor, GE Hinton, ST Roweis
Journal of Machine Learning Research 12 (Mar), 1025-1068, 2011
Improved regularization of convolutional neural networks with cutout
T DeVries, GW Taylor
arXiv preprint arXiv:1708.04552, 2017
Learning human identity from motion patterns
N Neverova, C Wolf, G Lacey, L Fridman, D Chandra, B Barbello, G Taylor
IEEE Access 4, 1810-1820, 2016
Deep learning on fpgas: Past, present, and future
G Lacey, GW Taylor, S Areibi
arXiv preprint arXiv:1602.04283, 2016
Automatic moth detection from trap images for pest management
W Ding, G Taylor
Computers and Electronics in Agriculture 123, 17-28, 2016
Dataset augmentation in feature space
T DeVries, GW Taylor
arXiv preprint arXiv:1702.05538, 2017
A multi-scale approach to gesture detection and recognition
N Neverova, C Wolf, G Paci, G Sommavilla, G Taylor, F Nebout
Proceedings of the IEEE International Conference on Computer Vision …, 2013
Learning invariance through imitation
GW Taylor, I Spiro, C Bregler, R Fergus
CVPR 2011, 2729-2736, 2011
Prediction of flow duration curves for ungauged basins
M Atieh, G Taylor, AMA Sattar, B Gharabaghi
Journal of hydrology 545, 383-394, 2017
Caffeinated FPGAs: FPGA framework for convolutional neural networks
R DiCecco, G Lacey, J Vasiljevic, P Chow, G Taylor, S Areibi
2016 International Conference on Field-Programmable Technology (FPT), 265-268, 2016
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Articles 1–20