4 citations · 4 across the 7 of their papers we have counts for
6 papers · 1 filter
Investigating the importance of county-level characteristics in opioid-related mortality across the United States
Andrew Deas, Adam Spannaus, Dakotah D. Maguire +3
The opioid crisis remains a critical public health challenge in the United States. Despite national efforts which reduced opioid prescribing rates by nearly 45\% between 2011 and 2…
Bayesian Sheaf Neural Networks
Patrick Gillespie, Layal Bou Hamdan, Ioannis Schizas +2
Equipping graph neural networks with a convolution operation defined in terms of a cellular sheaf offers advantages for learning expressive representations of heterophilic graph da…
Functional Ultrasound Imaging Combined with Machine Learning for Whole-Brain Analysis of Drug-Induced Hemodynamic Changes
Jared Deighton, Shan Zhong, Kofi Agyeman +5
Functional ultrasound imaging (fUSI) is a cutting-edge technology that measures changes in cerebral blood volume (CBV) by detecting backscattered echoes from red blood cells moving…
Identifying Spatiotemporal Patterns in Opioid Vulnerability: Investigating the Links Between Disability, Prescription Opioids and Opioid-Related Mortality
Andrew Deas, Hashan Fernando, Heidi A. Hanson +4
The opioid crisis remains one of the most daunting and complex public health problems in the United States. This study investigates the national epidemic by analyzing vulnerability…
Spectral-Stimulus Information for Self-Supervised Stimulus Encoding
Jared Deighton, Wyatt Mackey, Ioannis Schizas +2
Mammalian spatial navigation relies on specialized neurons, such as place and grid cells, which encode position based on self-motion and environmental cues. While extensive researc…
Geometric sparsification in recurrent neural networks
Wyatt Mackey, Ioannis Schizas, Jared Deighton +2
A common technique for ameliorating the computational costs of running large neural models is sparsification, or the pruning of neural connections during training. Sparse models ar…