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Differing effects of attention in single-units and populations are well predicted by heterogeneous tuning and the normalization model of attention., , and . Front. Comput. Neurosci., (2014)Shape Analysis of White Matter Tracts via the Laplace-Beltrami Spectrum., , , and . ShapeMI@@MICCAI, volume 11167 of Lecture Notes in Computer Science, page 195-206. Springer, (2018)Deconvolution of High Dimensional Mixtures via Boosting, with Application to Diffusion-Weighted MRI of Human Brain., , and . NIPS, page 2699-2707. (2014)Unified representation of tractography and diffusion-weighted MRI data using sparse multidimensional arrays., , , and . NIPS, page 4340-4351. (2017)Framework for shape analysis of white matter fiber bundles., , , , , and . NeuroImage, (2018)MPI-LiFE: Designing High-Performance Linear Fascicle Evaluation of Brain Connectome with MPI., , , , and . HiPC, page 213-222. IEEE Computer Society, (2017)White Matter Diffusion of Major Fiber Tracts Implicated in Autism Spectrum Disorder., , , , and . Brain Connectivity, 6 (9): 691-699 (2016)Ensemble Tractography., , , and . PLoS Computational Biology, (2016)Anatomically-Informed Multiple Linear Assignment Problems for White Matter Bundle Segmentation., , , , , and . ISBI, page 135-138. IEEE, (2019)ReAl-LiFE: Accelerating the Discovery of Individualized Brain Connectomes on GPUs., , , , and . AAAI, page 630-638. AAAI Press, (2019)