I lead the Machine Learning Research Group at the University of Guelph. I am interested in statistical machine learning and biologically-inspired computer vision, with an emphasis on deep learning and time series analysis.

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Research Highlights

A complete list of my publications is available on Google Scholar.

Weiguang Ding, Ruoyan Wang, Fei Mao, and Graham Taylor. Theano-based large-scale visual recognition with multiple GPUs. arXiv preprint arXiv:1412:2302, 2014. [ bib | .pdf ]

Weiguang Ding and Graham Taylor. Mental rotation by optimizing transforming distance. In Neural Information Processing Systems 27 (NIPS) Workshop on Deep Learning and Representation Learning, 2014. [ bib | .pdf ]

Jiwoong Im and Graham Taylor. Analyzing the dynamics of gated auto-encoders. In Neural Information Processing Systems 27 (NIPS) Workshop on Deep Learning and Representation Learning, 2014. [ bib | .pdf ]

Natalia Neverova, Christian Wolf, and Graham Taylor. Hand segmentation into parts with convolutional learning. In Asian Conference on Computer Vision (ACCV), 2014. [ bib | .pdf ]

Natalia Neverova, Christian Wolf, Graham Taylor, and Florian Nebout. Multi-scale deep learning for gesture detection and localization. In ECCV ChaLearn Workshop on Looking at People, 2014. [ bib | .pdf ]

Terrance Devries, Kumar Biswaranjan, and Graham Taylor. Multi-task learning of facial landmarks and expression. In 14th Canadian Conference on Computer and Robot Vision (CRV), 2014. [ bib | .pdf ]

Arjun Jain, Jonathan Tompson, Mykhaylo Andriluka, Graham Taylor, and Christoph Bregler. Learning human pose estimation features with convolutional networks. In International Conference on Learning Representations (ICLR), 2014. [ bib | .pdf ]

Group Members