Hang Gao

According to our database, Hang Gao authored at least 18 papers between 2022 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Unsupervised social event detection via hybrid graph contrastive learning and reinforced incremental clustering.

Yuanyuan Guo, Zehua Zang, Hang Gao, Xiao Xu, Rui Wang, Lixiang Liu, Jiangmeng Li

Knowl. Based Syst., 2024

Introducing diminutive causal structure into graph representation learning.

Hang Gao, Peng Qiao, Yifan Jin, Fengge Wu, Jiangmeng Li, Changwen Zheng

Knowl. Based Syst., 2024

Graph Partial Label Learning with Potential Cause Discovering.

Hang Gao, Jiaguo Yuan, Jiangmeng Li, Chengyu Yao, Fengge Wu, Junsuo Zhao, Changwen Zheng

CoRR, 2024

Molecular Graph Representation Learning via Structural Similarity Information.

Chengyu Yao, Hong Huang, Hang Gao, Fengge Wu, Haiming Chen, Junsuo Zhao

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2024

Learning Node Representations Under Partial Label Learning.

Jiaguo Yuan, Hang Gao, Fengge Wu, Junsuo Zhao

Proceedings of the International Joint Conference on Neural Networks, 2024

Discovering Symmetry Breaking in Physical Systems with Relaxed Group Convolution.

Rui Wang, Elyssa F. Hofgard, Hang Gao, Robin Walters, Tess E. Smidt

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Hierarchical Topology Isomorphism Expertise Embedded Graph Contrastive Learning.

Jiangmeng Li, Yifan Jin, Hang Gao, Wenwen Qiang, Changwen Zheng, Fuchun Sun

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Rethinking Causal Relationships Learning in Graph Neural Networks.

Hang Gao, Chengyu Yao, Jiangmeng Li, Lingyu Si, Yifan Jin, Fengge Wu, Changwen Zheng, Huaping Liu

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Information theory-guided heuristic progressive multi-view coding.

Jiangmeng Li, Hang Gao, Wenwen Qiang, Changwen Zheng

Neural Networks, October, 2023

Manifold-Guided Sampling in Diffusion Models for Unbiased Image Generation.

Xingzhe Su, Wenwen Qiang, Zeen Song, Hang Gao, Fengge Wu, Changwen Zheng

CoRR, 2023

A Unified GAN Framework Regarding Manifold Alignment for Remote Sensing Images Generation.

Xingzhe Su, Wenwen Qiang, Zeen Song, Hang Gao, Fengge Wu, Changwen Zheng

CoRR, 2023

Introducing Expertise Logic into Graph Representation Learning from A Causal Perspective.

Hang Gao, Jiangmeng Li, Wenwen Qiang, Lingyu Si, Xingzhe Su, Fengge Wu, Changwen Zheng, Fuchun Sun

CoRR, 2023

Introducing Semantic-Based Receptive Field into Semantic Segmentation via Graph Neural Networks.

Daixi Jia, Hang Gao, Xingzhe Su, Fengge Wu, Junsuo Zhao

Proceedings of the Neural Information Processing - 30th International Conference, 2023

SkaNet: Split Kernel Attention Network.

Lipeng Chen, Daixi Jia, Hang Gao, Fengge Wu, Junsuo Zhao

Proceedings of the Artificial Neural Networks and Machine Learning, 2023

Robust Causal Graph Representation Learning against Confounding Effects.

Hang Gao, Jiangmeng Li, Wenwen Qiang, Lingyu Si, Bing Xu, Changwen Zheng, Fuchun Sun

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Self-supervised Graph Learning with Segmented Graph Channels.

Hang Gao, Jiangmeng Li, Changwen Zheng

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

Bootstrapping Informative Graph Augmentation via A Meta Learning Approach.

Hang Gao, Jiangmeng Li, Wenwen Qiang, Lingyu Si, Fuchun Sun, Changwen Zheng

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Weight-Aware Graph Contrastive Learning.

Hang Gao, Jiangmeng Li, Peng Qiao, Changwen Zheng

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2022, 2022