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20182026
most citedClassification of EEG-Based Brain Connectivity Networks in Schizophrenia Using a Multi-Domain Connectome Convolutional Neural Network

189 citations · 470 across the 13 of their papers we have counts for

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5 papers · 1 filter

cs.LG2026

Structural-Functional Brain Connectivity Generation via Multimodal Hypergraph-based Flow Matching

Chyong Yi Poh, Hwa Hui Tew, Junn Yong Loo +4

Structural connectivity (SC) and functional connectivity (FC) provide complementary information on interactions between brain regions and are widely used in neuroimaging studies of…

cs.LG2025

T2I-Diff: fMRI Signal Generation via Time-Frequency Image Transform and Classifier-Free Denoising Diffusion Models

Hwa Hui Tew, Junn Yong Loo, Yee-Fan Tan +5

Functional Magnetic Resonance Imaging (fMRI) is an advanced neuroimaging method that enables in-depth analysis of brain activity by measuring dynamic changes in the blood oxygenati…

cs.LG2023

A Deep Probabilistic Spatiotemporal Framework for Dynamic Graph Representation Learning with Application to Brain Disorder Identification

Sin-Yee Yap, Junn Yong Loo, Chee-Ming Ting +4

Recent applications of pattern recognition techniques on brain connectome classification using functional connectivity (FC) are shifting towards acknowledging the non-Euclidean top…

cs.LG2022★ 8 cited

Graph-Regularized Manifold-Aware Conditional Wasserstein GAN for Brain Functional Connectivity Generation

Yee-Fan Tan, Chee-Ming Ting, Fuad Noman +2

Common measures of brain functional connectivity (FC) including covariance and correlation matrices are semi-positive definite (SPD) matrices residing on a cone-shape Riemannian ma…

cs.LG2019★ 189 cited

Classification of EEG-Based Brain Connectivity Networks in Schizophrenia Using a Multi-Domain Connectome Convolutional Neural Network

Chun-Ren Phang, Chee-Ming Ting, Fuad Noman +1

We exploit altered patterns in brain functional connectivity as features for automatic discriminative analysis of neuropsychiatric patients. Deep learning methods have been introdu…