11 citations · 12 across the 5 of their papers we have counts for
5 papers
Accounting for Temporal Variability in Functional Magnetic Resonance Imaging Improves Prediction of Intelligence
Yang Li, Xin Ma, Raj Sunderraman +2
Neuroimaging-based prediction methods for intelligence and cognitive abilities have seen a rapid development in literature. Among different neuroimaging modalities, prediction base…
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…
Separating Boundary Points via Structural Regularization for Very Compact Clusters
Xin Ma, Won Hwa Kim
Clustering algorithms have significantly improved along with Deep Neural Networks which provide effective representation of data. Existing methods are built upon deep autoencoder a…
Multi-task Learning with High-Dimensional Noisy Images
Xin Ma, Suprateek Kundu
Recent medical imaging studies have given rise to distinct but inter-related datasets corresponding to multiple experimental tasks or longitudinal visits. Standard scalar-on-image…
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…