| Improved Regularization of Convolutional Neural Networks with Cutout T DeVries arXiv preprint arXiv:1708.04552, 2017 | 4363 | 2017 |
| Deconvolutional networks MD Zeiler, D Krishnan, GW Taylor, R Fergus Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on …, 2010 | 2339 | 2010 |
| Adaptive deconvolutional networks for mid and high level feature learning MD Zeiler, GW Taylor, R Fergus 2011 international conference on computer vision, 2018-2025, 2011 | 1696 | 2011 |
| Modeling human motion using binary latent variables GW Taylor, GE Hinton, S Roweis Advances in neural information processing systems 19, 2006 | 1030 | 2006 |
| Deep multimodal learning: A survey on recent advances and trends D Ramachandram, GW Taylor IEEE signal processing magazine 34 (6), 96-108, 2017 | 955 | 2017 |
| Convolutional learning of spatio-temporal features GW Taylor, R Fergus, Y LeCun, C Bregler Computer Vision–ECCV 2010: 11th European Conference on Computer Vision …, 2010 | 897 | 2010 |
| Learning confidence for out-of-distribution detection in neural networks T DeVries, GW Taylor arXiv preprint arXiv:1802.04865, 2018 | 648 | 2018 |
| The recurrent temporal restricted boltzmann machine I Sutskever, GE Hinton, GW Taylor Advances in neural information processing systems 21, 2008 | 606 | 2008 |
| Dataset augmentation in feature space T DeVries, GW Taylor arXiv preprint arXiv:1702.05538, 2017 | 548 | 2017 |
| Factored conditional restricted Boltzmann machines for modeling motion style GW Taylor, GE Hinton Proceedings of the 26th annual international conference on machine learning …, 2009 | 517 | 2009 |
| 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 | 439 | 2015 |
| Automatic moth detection from trap images for pest management W Ding, G Taylor Computers and Electronics in Agriculture 123, 17-28, 2016 | 389 | 2016 |
| Understanding attention and generalization in graph neural networks B Knyazev, GW Taylor, M Amer Advances in neural information processing systems 32, 2019 | 368 | 2019 |
| Forecasting air quality time series using deep learning BS Freeman, G Taylor, B Gharabaghi, J Thé Journal of the Air & Waste Management Association 68 (8), 866-886, 2018 | 303 | 2018 |
| Multi-scale deep learning for gesture detection and localization N Neverova, C Wolf, GW Taylor, F Nebout Computer Vision-ECCV 2014 Workshops: Zurich, Switzerland, September 6-7 and …, 2015 | 297 | 2015 |
| Federated learning and differential privacy for medical image analysis M Adnan, S Kalra, JC Cresswell, GW Taylor, HR Tizhoosh Scientific reports 12 (1), 1953, 2022 | 267 | 2022 |
| Learning human pose estimation features with convolutional networks A Jain, J Tompson, M Andriluka, GW Taylor, C Bregler arXiv preprint arXiv:1312.7302, 2013 | 256 | 2013 |
| Deep learning on FPGAs: Past, present, and future G Lacey, GW Taylor, S Areibi arXiv preprint arXiv:1602.04283, 2016 | 250 | 2016 |
| 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 | 225 | 2016 |
| Deep learning object detection methods for ecological camera trap data S Schneider, GW Taylor, S Kremer 2018 15th Conference on computer and robot vision (CRV), 321-328, 2018 | 217 | 2018 |
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