Temporal Graph Representation Learning for Autism spectrum disorder Brain Networks. - Peng Cao 001; Guangqi Wen; Lanting Li; Xiaoli Liu 001; Jinzhu Yang; Osmar Zaïane (BIBM, 2021)

DGE-GSIM: A multi-task dual graph embedding learning for graph similarity computation. - Wenhui Tan; Peng Cao 001; Zhiyong Jin; Futao Luo; Guangqi Wen; Weiping Li (ICMLSC, 2022)

MVS-GCN: A prior brain structure learning-guided multi-view graph convolution network for autism spectrum disorder diagnosis. - Guangqi Wen; Peng Cao 001; Huiwen Bao; Wenju Yang; Tong Zheng 006; Osmar Zaïane (Comput. Biol. Medicine, 2022)

Collaborative learning of graph generation, clustering and classification for brain networks diagnosis. - Wenju Yang; Guangqi Wen; Peng Cao 001; Jinzhu Yang; Osmar R. Zaïane (Comput. Methods Programs Biomed., 2022)

Modeling the dynamic brain network representation for autism spectrum disorder diagnosis. - Peng Cao 001; Guangqi Wen; Xiaoli Liu 001; Jinzhu Yang; Osmar R. Zaïane (Medical Biol. Eng. Comput., 2022)

TE-HI-GCN: An Ensemble of Transfer Hierarchical Graph Convolutional Networks for Disorder Diagnosis. - Lanting Li; Hao Jiang; Guangqi Wen; Peng Cao 001; MingYi Xu; Xiaoli Liu 001; Jinzhu Yang; Osmar R. Zaïane (Neuroinformatics, 2022)

Towards Time-Variant-Aware Link Prediction in Dynamic Graph Through Self-supervised Learning. - Guangqi Wen; Peng Cao 001; Zhiyong Jin; Ruoxian Song; Xiaoli Liu 001; Jinzhu Yang; Osmar R. Zaïane (ADMA (4), 2023)

BrainUSL: Unsupervised Graph Structure Learning for Functional Brain Network Analysis. - Pengshuai Zhang; Guangqi Wen; Peng Cao 001; Jinzhu Yang; Jinyu Zhang; Xizhe Zhang; Xinrong Zhu; Osmar R. Zaïane; Fei Wang 064 (MICCAI (8), 2023)

MS-SSD: multi-scale single shot detector for ship detection in remote sensing images. - Guangqi Wen; Peng Cao 001; Haonan Wang; Hanlin Chen; Xiaoli Liu 001; Jinghui Xu; Osmar R. Zaïane (Appl. Intell., 2023)

Exploring attention mechanism for graph similarity learning. - Wenhui Tan; Xin Gao; Yiyang Li; Guangqi Wen; Peng Cao 001; Jinzhu Yang; Weiping Li; Osmar R. Zaïane (Knowl. Based Syst., 2023)

BrainTGL: A dynamic graph representation learning model for brain network analysis. - Lingwen Liu; Guangqi Wen; Peng Cao 001; Tianshun Hong; Jinzhu Yang; Xizhe Zhang; Osmar R. Zaïane (Comput. Biol. Medicine, 2023)

A unified framework of graph structure learning, graph generation and classification for brain network analysis. - Peng Cao 001; Guangqi Wen; Wenju Yang; Xiaoli Liu 001; Jinzhu Yang; Osmar R. Zaïane (Appl. Intell., 2023)

Exploring interpretable graph convolutional networks for autism spectrum disorder diagnosis. - Lanting Li; Guangqi Wen; Peng Cao 001; Xiaoli Liu 001; Osmar R. Zaïane; Jinzhu Yang (Int. J. Comput. Assist. Radiol. Surg., 2023)

Graph Self-Supervised Learning With Application to Brain Networks Analysis. - Guangqi Wen; Peng Cao 001; Lingwen Liu; Jinzhu Yang; Xizhe Zhang; Fei Wang 064; Osmar R. Zaïane (IEEE J. Biomed. Health Informatics, 2023)

Towards Disease-Aware Self-Supervised Dynamic Brain Network Learning For Mental Diagnosis. - Zhiyong Jin; Guangqi Wen; Peng Cao 001; Lingwen Liu; Jinzhu Yang; Xinrong Zhu; Osmar R. Zaïane; Fei Wang 064 (ICASSP, 2024)

Capturing Temporal Node Evolution via Self-supervised Learning: A New Perspective on Dynamic Graph Learning. - Lingwen Liu; Guangqi Wen; Peng Cao 001; Jinzhu Yang; Weiping Li; Osmar R. Zaïane (WSDM, 2024)

BrainDAS: Structure-aware domain adaptation network for multi-site brain network analysis. - Ruoxian Song; Peng Cao 001; Guangqi Wen; Pengfei Zhao; Ziheng Huang; Xizhe Zhang; Jinzhu Yang; Osmar R. Zaïane (Medical Image Anal., 2024)

Heterogeneous Graph Representation Learning Framework for Resting-State Functional Connectivity Analysis. - Guangqi Wen; Peng Cao 001; Lingwen Liu; Maochun Hao; Siyu Liu; Junjie Zheng; Jinzhu Yang; Osmar R. Zaïane; Fei Wang 064 (IEEE Trans. Medical Imaging, 2025)

Exploring Attention and Self-Supervised Learning Mechanism for Graph Similarity Learning. - Guangqi Wen; Xin Gao; Wenhui Tan; Peng Cao 001; Jinzhu Yang; Weiping Li; Osmar R. Zaïane (IEEE Trans. Neural Networks Learn. Syst., 2025)