38 citations · 40 across the 5 of their papers we have counts for
10 papers
High-dimensional Measurement Error Models for Lipschitz Loss
Xin Ma, Suprateek Kundu
Recently emerging large-scale biomedical data pose exciting opportunities for scientific discoveries. However, the ultrahigh dimensionality and non-negligible measurement errors in…
Evaluating the Performance of StyleGAN2-ADA on Medical Images
McKell Woodland, John Wood, Brian M. Anderson +12
Although generative adversarial networks (GANs) have shown promise in medical imaging, they have four main limitations that impeded their utility: computational cost, data requirem…
Flexible Bayesian Support Vector Machines for Brain Network-based Classification
Jin Ming, Suprateek Kundu
Objective: Brain networks have gained increasing recognition as potential biomarkers in mental health studies, but there are limited approaches that can leverage complex brain netw…
Elastic Shape Analysis of Brain Structures for Predictive Modeling of PTSD
Yuexuan Wu, Suprateek Kundu, Jennifer S. Stevens +2
There is increasing evidence on the importance of brain morphology in predicting and classifying mental disorders. However, the vast majority of current shape approaches rely heavi…
Integrative Learning for Population of Dynamic Networks with Covariates
Suprateek Kundu, Jin Ming, Joe Nocera +1
Although there is a rapidly growing literature on dynamic connectivity methods, the primary focus has been on separate network estimation for each individual, which fails to levera…
Semi-parametric Bayes Regression with Network Valued Covariates
Xin Ma, Suprateek Kundu, Jennifer Stevens
There is an increasing recognition of the role of brain networks as neuroimaging biomarkers in mental health and psychiatric studies. Our focus is posttraumatic stress disorder (PT…