• Publications
  • Software
  • Data Sets
  • Training Resources

Filter by:






Results for: Publications | Neuroimage-based Phenotyping Project


Statistical tests and identifiability conditions for pooling and analyzing multisite datasets. Zhou HH, Singh V, Johnson SC, Wahba G, and the Alzheimer’s Disease Neuroimaging Initiative. Proceedings of the National Academy of Sciences USA, 2018.

A geometric framework for statistical analysis of trajectories with distinct temporal spans. Chakraborty R, Singh V, Adluru N, Vemuri B. Proceedings of the International Conference on Computer Vision (ICCV), 2017.

Accelerating permutation testing in voxel-wise analysis through subspace tracking: A new plugin for SnPM. Gutierrez-Barragan F, Ithapu VK, Hinrichs C, Maumet C, Johnson SC, Nichols TE, Singh V. Neuroimage 159(1):79-98, 2017.

Modeling cognitive trends in preclinical Alzheimer's disease (AD) via distributions over permutations. Plumb G, Clark LR, Johnson SC, Singh V. Proceedings of Medical Image Computing And Computer Assisted Intervention (MICCAI), 2017.

When can multi-site datasets be pooled for regression? Hypothesis tests, L2-consistency and neuroscience applications. Zhou HH, Zhang Y, Ithapu VK, Johnson SC, Wahba G, Singh V. Proceedings of the International Conference on Machine Learning (ICML), 2017.

Riemannian nonlinear mixed effects models: analyzing longitudinal deformations in neuroimaging. Kim HJ, Adluru N, Suri H, Vemuri BC, Johnson SC, Singh V. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017.

Riemannian variance filtering: An independent filtering scheme for statistical tests on manifold-valued data. Zheng L, Kim HJ, Adluru N, Newton MA, Singh V. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2017.

The incremental multiresolution matrix factorization algorithm. Ithapu VK, Kondor R, Johnson SC, Singh V. Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , 2017.

Hypothesis testing in unsupervised domain adaptation with applications in neuroimaging. Zhou H, Ravi S, Ithapu V, Johnson S, Wahba G, Singh V. Advances in Neural Information Processing Systems (NIPS), 2016.

Adaptive signal recovery on graphs via harmonic analysis for experimental design in neuroimaging. Kim WH, Hwang SJ, Adluru N, Johnson SC, Singh V. Proceedings of the 14th European Conference on Computer Vision (ECCV), Volume 9910 Lecture Notes in Computer Science, 2016.

Next Page