Understanding Graph Neural Networks from Graph Signal Denoising Perspectives. - Guoji Fu; Yifan Hou; Jie Zhang 046; Kaili Ma 001; Barakeel Fanseu Kamhoua; James Cheng (CoRR, 2020)

HyperGraph Convolution Based Attributed HyperGraph Clustering. - Barakeel Fanseu Kamhoua; Lin Zhang; Kaili Ma 001; James Cheng; Bo Li 001; Bo Han 003 (CIKM, 2021)

Improving Graph Representation Learning by Contrastive Regularization. - Kaili Ma 001; Haochen Yang; Han Yang 002; Tatiana Jin; Pengfei Chen; Yongqiang Chen 002; Barakeel Fanseu Kamhoua; James Cheng (CoRR, 2021)

Exact Shape Correspondence via 2D graph convolution. - Barakeel Fanseu Kamhoua; Lin Zhang; Yongqiang Chen 002; Han Yang 002; Kaili Ma 001; Bo Han 003; Bo Li 001; James Cheng (NeurIPS, 2022)

GRACE: A General Graph Convolution Framework for Attributed Graph Clustering. - Barakeel Fanseu Kamhoua; Lin Zhang; Kaili Ma 001; James Cheng; Bo Li 001; Bo Han 003 (ACM Trans. Knowl. Discov. Data, 2023)

HOPE: Shape Matching Via Aligning Different K-hop Neighbourhoods. - Barakeel Fanseu Kamhoua; Huamin Qu (NeurIPS, 2024)