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20172023
most citedAdversarial Attack on Hierarchical Graph Pooling Neural Networks

22 citations · 43 across the 11 of their papers we have counts for

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5 papers · 1 filter

cs.LG2022★ 1 cited

Tensor-Based Multi-Modality Feature Selection and Regression for Alzheimer's Disease Diagnosis

Jun Yu, Zhaoming Kong, Liang Zhan +2

The assessment of Alzheimer's Disease (AD) and Mild Cognitive Impairment (MCI) associated with brain changes remains a challenging task. Recent studies have demonstrated that combi…

cs.LG2022

Functional2Structural: Cross-Modality Brain Networks Representation Learning

Haoteng Tang, Xiyao Fu, Lei Guo +7

MRI-based modeling of brain networks has been widely used to understand functional and structural interactions and connections among brain regions, and factors that affect them, su…

cs.LG2020★ 4 cited

CommPOOL: An Interpretable Graph Pooling Framework for Hierarchical Graph Representation Learning

Haoteng Tang, Guixiang Ma, Lifang He +2

Recent years have witnessed the emergence and flourishing of hierarchical graph pooling neural networks (HGPNNs) which are effective graph representation learning approaches for gr…

cs.LG2020★ 22 cited

Adversarial Attack on Hierarchical Graph Pooling Neural Networks

Haoteng Tang, Guixiang Ma, Yurong Chen +4

Recent years have witnessed the emergence and development of graph neural networks (GNNs), which have been shown as a powerful approach for graph representation learning in many ta…

cs.LG2018

Subspace Network: Deep Multi-Task Censored Regression for Modeling Neurodegenerative Diseases

Mengying Sun, Inci M. Baytas, Liang Zhan +2

Over the past decade a wide spectrum of machine learning models have been developed to model the neurodegenerative diseases, associating biomarkers, especially non-intrusive neuroi…