32 citations · 120 across the 18 of their papers we have counts for
5 papers · 1 filter
Sparsely Grouped Input Variables for Neural Networks
Beibin Li, Nicholas Nuechterlein, Erin Barney +4
In genomic analysis, biomarker discovery, image recognition, and other systems involving machine learning, input variables can often be organized into different groups by their sou…
Graph Embedding Using Infomax for ASD Classification and Brain Functional Difference Detection
Xiaoxiao Li, Nicha C. Dvornek, Juntang Zhuang +2
Significant progress has been made using fMRI to characterize the brain changes that occur in ASD, a complex neuro-developmental disorder. However, due to the high dimensionality a…
Invertible Network for Classification and Biomarker Selection for ASD
Juntang Zhuang, Nicha C. Dvornek, Xiaoxiao Li +2
Determining biomarkers for autism spectrum disorder (ASD) is crucial to understanding its mechanisms. Recently deep learning methods have achieved success in the classification tas…
Graph Neural Network for Interpreting Task-fMRI Biomarkers
Xiaoxiao Li, Nicha C. Dvornek, Yuan Zhou +3
Finding the biomarkers associated with ASD is helpful for understanding the underlying roots of the disorder and can lead to earlier diagnosis and more targeted treatment. A promis…
A Facial Affect Analysis System for Autism Spectrum Disorder
Beibin Li, Sachin Mehta, Deepali Aneja +4
In this paper, we introduce an end-to-end machine learning-based system for classifying autism spectrum disorder (ASD) using facial attributes such as expressions, action units, ar…