most citedBrain Network Transformer

56 citations · 159 across the 9 of their papers we have counts for

collaborators

9 papers

q-bio.NC20225 cited

Learning Task-Aware Effective Brain Connectivity for fMRI Analysis with Graph Neural Networks

Yue Yu, Xuan Kan, Hejie Cui +9

Functional magnetic resonance imaging (fMRI) has become one of the most common imaging modalities for brain function analysis. Recently, graph neural networks (GNN) have been adopt…

cs.LG202256 cited

Brain Network Transformer

Xuan Kan, Wei Dai, Hejie Cui +3

Human brains are commonly modeled as networks of Regions of Interest (ROIs) and their connections for the understanding of brain functions and mental disorders. Recently, Transform…

cs.LG202229 cited

FBNETGEN: Task-aware GNN-based fMRI Analysis via Functional Brain Network Generation

Xuan Kan, Hejie Cui, Joshua Lukemire +2

Functional magnetic resonance imaging (fMRI) is one of the most common imaging modalities to investigate brain functions. Recent studies in neuroscience stress the great potential…

cs.IR2022

How Can Graph Neural Networks Help Document Retrieval: A Case Study on CORD19 with Concept Map Generation

Hejie Cui, Jiaying Lu, Yao Ge +1

Graph neural networks (GNNs), as a group of powerful tools for representation learning on irregular data, have manifested superiority in various downstream tasks. With unstructured…

cs.LG20213 cited

Structure-Aware Hard Negative Mining for Heterogeneous Graph Contrastive Learning

Yanqiao Zhu, Yichen Xu, Hejie Cui +3

Recently, heterogeneous Graph Neural Networks (GNNs) have become a de facto model for analyzing HGs, while most of them rely on a relative large number of labeled data. In this wor…

cs.LG20212 cited

Effective and Interpretable fMRI Analysis via Functional Brain Network Generation

Xuan Kan, Hejie Cui, Ying Guo +1

Recent studies in neuroscience show great potential of functional brain networks constructed from fMRI data for popularity modeling and clinical predictions. However, existing func…