2 citations · 3 across the 5 of their papers we have counts for
5 papers
Alignment of Continuous Brain Connectivity
Martin Cole, Yang Xiang, Will Consagra +3
Brain networks are typically represented by adjacency matrices, where each node corresponds to a brain region. In traditional brain network analysis, nodes are assumed to be matche…
NeuroPMD: Neural Fields for Density Estimation on Product Manifolds
William Consagra, Zhiling Gu, Zhengwu Zhang
We propose a novel deep neural network methodology for density estimation on product Riemannian manifold domains. In our approach, the network directly parameterizes the unknown de…
Continuous and Atlas-free Analysis of Brain Structural Connectivity
William Consagra, Martin Cole, Xing Qiu +1
Brain structural networks are often represented as discrete adjacency matrices with elements summarizing the connectivity between pairs of regions of interest (ROIs). These ROIs ar…
Analyzing Brain Structural Connectivity as Continuous Random Functions
William Consagra, Martin Cole, Zhengwu Zhang
This work considers a continuous framework to characterize the population-level variability of structural connectivity. Our framework assumes the observed white matter fiber tract…
Efficient Multidimensional Functional Data Analysis Using Marginal Product Basis Systems
William Consagra, Arun Venkataraman, Xing Qiu
Many modern datasets, from areas such as neuroimaging and geostatistics, come in the form of a random sample of tensor-valued data which can be understood as noisy observations of…