Graham Taylor
Graham Taylor
University of Guelph and Vector Institute for Artificial Intelligence
Verified email at uoguelph.ca - Homepage
TitleCited byYear
Deconvolutional networks
MD Zeiler, D Krishnan, GW Taylor, R Fergus
Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on …, 2010
9812010
Adaptive deconvolutional networks for mid and high level feature learning.
MD Zeiler, GW Taylor, R Fergus
ICCV 1 (2), 6, 2011
7682011
Modeling human motion using binary latent variables
GW Taylor, GE Hinton, ST Roweis
Advances in neural information processing systems, 1345-1352, 2007
7152007
Convolutional learning of spatio-temporal features
GW Taylor, R Fergus, Y LeCun, C Bregler
European conference on computer vision, 140-153, 2010
5532010
The recurrent temporal restricted boltzmann machine
I Sutskever, GE Hinton, GW Taylor
Advances in neural information processing systems, 1601-1608, 2009
3592009
Factored conditional restricted Boltzmann machines for modeling motion style
GW Taylor, GE Hinton
Proceedings of the 26th annual international conference on machine learning …, 2009
3442009
Improved regularization of convolutional neural networks with cutout
T DeVries, GW Taylor
arXiv preprint arXiv:1708.04552, 2017
2292017
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
1652014
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, 2015
1572015
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
1402010
Learning human pose estimation features with convolutional networks
A Jain, J Tompson, M Andriluka, GW Taylor, C Bregler
arXiv preprint arXiv:1312.7302, 2013
1332013
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
1072011
Deep learning on fpgas: Past, present, and future
G Lacey, GW Taylor, S Areibi
arXiv preprint arXiv:1602.04283, 2016
852016
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
842016
Automatic moth detection from trap images for pest management
W Ding, G Taylor
Computers and Electronics in Agriculture 123, 17-28, 2016
802016
Dataset augmentation in feature space
T DeVries, GW Taylor
arXiv preprint arXiv:1702.05538, 2017
782017
Learning confidence for out-of-distribution detection in neural networks
T DeVries, GW Taylor
arXiv preprint arXiv:1802.04865, 2018
562018
Deep multimodal learning: A survey on recent advances and trends
D Ramachandram, GW Taylor
IEEE Signal Processing Magazine 34 (6), 96-108, 2017
552017
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
552013
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
492016
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