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Barbara B. Bendlin

3 accepted papers

2019

Dilated Convolutional Neural Networks for Sequential Manifold-Valued Data

ICCV 2019accepted

Efforts are underway to study ways via which the power of deep neural networks can be extended to non-standard data types such as structured data (e.g., graphs) or manifold-valued data (e.g., unit vectors or special matrices). Often, sizable empirical improvements are possible when the geometry of s…

2016

Coupled Harmonic Bases for Longitudinal Characterization of Brain Networks

CVPR 2016poster

There is a great deal of interest in using large scale brain imaging studies to understand how brain connectivity evolves over time for an individual and how it varies over different levels/quantiles of cognitive function. To do so, one typically performs so-called tractography procedures on diffusi…

Cited by 9PDFScholar
2015

Statistical Inference Models for Image Datasets With Systematic Variations

CVPR 2015poster

Statistical analysis of longitudinal or cross sectionalbrain imaging data to identify effects of neurodegenerative diseases is a fundamental task in various studies in neuroscience. However, when there are systematic variations in the images due to parameters changes such as changes in the scanner p…

Cited by 9SourcePDFScholar