Garrett T. Kenyon

P-21 Biophysics Los Alamos National Laboratory, Los Alamos, NM, United States 
computational neuroscience
"Garrett Kenyon"
Mean distance: 106866 (cluster 17)
Cross-listing: Computational Biology Tree


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Dan N. Hill research assistant Technical University of Munich
Bartlett D. Moore IV research assistant 2001-2002 LANL
Dylan M Paiton research assistant 2011-2013 LANL
Greg Stephens post-doc LANL (Physics Tree)
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Völgyi B, Kenyon GT, Marshak DW, et al. (2019) Editorial: Encoding Visual Features by Parallel Ganglion Cell Initiated Pathways in the Healthy, Diseased and Artificial Retina. Frontiers in Cellular Neuroscience. 13: 229
Ji Z, Theiler J, Chartrand R, et al. (2013) Decoupling sparse coding of SIFT descriptors for large-scale visual recognition Proceedings of Spie. 8750
Lundquist SY, Paiton DM, Nowers BM, et al. (2013) Biologically inspired distributed sensor networks: Collective signal amplification via ultra-low bandwidth spike-based communication Proceedings of the International Joint Conference On Neural Networks
Ji Z, Brumby SP, Kenyon G, et al. (2012) Integrating Bottom-up and Top-down Visual Attention for Object Segmentation Journal of Vision. 12: 926-926
Paiton DM, Brumby SP, Kenyon GT, et al. (2012) Combining multiple visual processing streams for locating and classifying objects in video Proceedings of the Ieee Southwest Symposium On Image Analysis and Interpretation. 49-52
Gintautas V, Ham MI, Kunsberg B, et al. (2011) Model cortical association fields account for the time course and dependence on target complexity of human contour perception Plos Computational Biology. 7
Ham M, Brumby S, Ji Z, et al. (2011) Task-specific saliency from sparse, hierarchical models of visual cortex compared to eye-tracking data for object detection in natural video sequences Journal of Vision. 11: 1281-1281
Brumby SP, Ham MI, Landecker WA, et al. (2011) Visualizing classification of natural video sequences using sparse, hierarchical models of cortex. Nature Precedings. 6: 1-1
Kenyon GT. (2010) Extreme synergy: Spatiotemporal correlations enable rapid image reconstruction from computer-generated spike trains Journal of Vision. 10: 1-27
Kenyon G, Barr S, Ham M, et al. (2010) Top-down models explain key aspects of a Speed-of-Sight character recognition task Journal of Vision. 10: 985-985
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