Weight-Aware Graph Contrastive Learning. - Hang Gao 004; Jiangmeng Li; Peng Qiao; Changwen Zheng (ICANN (2), 2022)

Bootstrapping Informative Graph Augmentation via A Meta Learning Approach. - Hang Gao 004; Jiangmeng Li; Wenwen Qiang; Lingyu Si; Fuchun Sun 001; Changwen Zheng (IJCAI, 2022)

Self-supervised Graph Learning with Segmented Graph Channels. - Hang Gao 004; Jiangmeng Li; Changwen Zheng (ECML/PKDD (2), 2022)

Robust Causal Graph Representation Learning against Confounding Effects. - Hang Gao 004; Jiangmeng Li; Wenwen Qiang; Lingyu Si; Bing Xu; Changwen Zheng; Fuchun Sun 001 (AAAI, 2023)

SkaNet: Split Kernel Attention Network. - Lipeng Chen; Daixi Jia; Hang Gao 004; Fengge Wu; Junsuo Zhao (ICANN (5), 2023)

Introducing Semantic-Based Receptive Field into Semantic Segmentation via Graph Neural Networks. - Daixi Jia; Hang Gao 004; Xingzhe Su; Fengge Wu; Junsuo Zhao (ICONIP (6), 2023)

Introducing Expertise Logic into Graph Representation Learning from A Causal Perspective. - Hang Gao 004; Jiangmeng Li; Wenwen Qiang; Lingyu Si; Xingzhe Su; Fengge Wu; Changwen Zheng; Fuchun Sun 001 (CoRR, 2023)

A Unified GAN Framework Regarding Manifold Alignment for Remote Sensing Images Generation. - Xingzhe Su; Wenwen Qiang; Zeen Song; Hang Gao 004; Fengge Wu; Changwen Zheng (CoRR, 2023)

Manifold-Guided Sampling in Diffusion Models for Unbiased Image Generation. - Xingzhe Su; Wenwen Qiang; Zeen Song; Hang Gao 004; Fengge Wu; Changwen Zheng (CoRR, 2023)

Information theory-guided heuristic progressive multi-view coding. - Jiangmeng Li; Hang Gao 004; Wenwen Qiang; Changwen Zheng (Neural Networks, 2023)

Rethinking Causal Relationships Learning in Graph Neural Networks. - Hang Gao 004; Chengyu Yao; Jiangmeng Li; Lingyu Si; Yifan Jin; Fengge Wu; Changwen Zheng; Huaping Liu 001 (AAAI, 2024)

Hierarchical Topology Isomorphism Expertise Embedded Graph Contrastive Learning. - Jiangmeng Li; Yifan Jin; Hang Gao 004; Wenwen Qiang; Changwen Zheng; Fuchun Sun 001 (AAAI, 2024)

Discovering Symmetry Breaking in Physical Systems with Relaxed Group Convolution. - Rui Wang 086; Elyssa F. Hofgard; Hang Gao 004; Robin Walters 001; Tess E. Smidt (ICML, 2024)

Learning Node Representations Under Partial Label Learning. - Jiaguo Yuan; Hang Gao 004; Fengge Wu; Junsuo Zhao (IJCNN, 2024)

Molecular Graph Representation Learning via Structural Similarity Information. - Chengyu Yao; Hong Huang 004; Hang Gao 004; Fengge Wu; Haiming Chen 001; Junsuo Zhao (ECML/PKDD (3), 2024)

Graph Partial Label Learning with Potential Cause Discovering. - Hang Gao 004; Jiaguo Yuan; Jiangmeng Li; Chengyu Yao; Fengge Wu; Junsuo Zhao; Changwen Zheng (CoRR, 2024)

Introducing diminutive causal structure into graph representation learning. - Hang Gao 004; Peng Qiao; Yifan Jin; Fengge Wu; Jiangmeng Li; Changwen Zheng (Knowl. Based Syst., 2024)

Unsupervised social event detection via hybrid graph contrastive learning and reinforced incremental clustering. - Yuanyuan Guo; Zehua Zang; Hang Gao 004; Xiao Xu; Rui Wang 086; Lixiang Liu; Jiangmeng Li (Knowl. Based Syst., 2024)

Bootstrapping Heterogeneous Graph Representation Learning via Large Language Models: A Generalized Approach. - Hang Gao 004; Chenhao Zhang; Fengge Wu; Changwen Zheng; Junsuo Zhao; Huaping Liu 001 (AAAI, 2025)

Learn to Think: Bootstrapping LLM Reasoning Capability Through Graph Representation Learning. - Hang Gao 004; Chenhao Zhang; Tie Wang; Junsuo Zhao; Fengge Wu; Changwen Zheng; Huaping Liu 001 (CoRR, 2025)

Large Language Model Enhancers for Graph Neural Networks: An Analysis from the Perspective of Causal Mechanism Identification. - Hang Gao 004; Wenxuan Huang; Fengge Wu; Junsuo Zhao; Changwen Zheng; Huaping Liu 001 (CoRR, 2025)