Weigang Lu

Orcid: 0000-0003-4855-7070

Affiliations:

Hong Kong University of Science and Technology (HKUST), Department of Civil and Environmental Engineering, Hong Kong
Xidian University, Xi'an, China (PhD)

According to our database¹, Weigang Lu authored at least 22 papers between 2021 and 2026.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

Legend:

Book In proceedings Article PhD thesis Dataset Other

Bibliography

2026

Does noise in the knowledge graph really harm recommendations?

[BibT_eX]

[DOI]

Pattern Recognit., 2026

Beyond Single-Granularity Prompts: A Multi-Scale Chain-of-Thought Prompt Learning for Graph.

[BibT_eX]

[DOI]

Proceedings of the ACM Web Conference 2026, 2026

Aligning Multiple Knowledge Graphs in A Single Pass.

[BibT_eX]

[DOI]

Proceedings of the ACM Web Conference 2026, 2026

MessageShift: Fine-Grained Data Augmentation for Graph Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the ACM Web Conference 2026, 2026

Collaborative Pattern Mining in Activity Graphs.

[BibT_eX]

[DOI]

Proceedings of the Database Systems for Advanced Applications, 2026

ProGMLP: A Progressive Framework for GNN-to-MLP Knowledge Distillation with Efficient Trade-offs.

[BibT_eX]

[DOI]

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

Higher-order interactions of multi-layer prompt.

[BibT_eX]

[DOI]

CoRR, October, 2025

Pseudo Contrastive Learning for graph-based semi-supervised learning.

[BibT_eX]

[DOI]

Neurocomputing, 2025

G-NodeMixup: Enhancing graph neural networks reachability under extremely limited labels.

[BibT_eX]

[DOI]

Neurocomputing, 2025

Enhancing Homophily-Heterophily Separation: Relation-Aware Learning in Heterogeneous Graphs.

[BibT_eX]

[DOI]

Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.2, 2025

Discrepancy-Aware Graph Mask Auto-Encoder.

[BibT_eX]

[DOI]

Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.2, 2025

A Translation-Based Heterogeneous Graph Neural Network for Multiple Knowledge Graphs Alignment.

[BibT_eX]

[DOI]

Proceedings of the 41st IEEE International Conference on Data Engineering, 2025

SkipNode: On Alleviating Performance Degradation for Deep Graph Convolutional Networks (Extended Abstract).

[BibT_eX]

[DOI]

Proceedings of the 41st IEEE International Conference on Data Engineering, 2025

AGMixup: Adaptive Graph Mixup for Semi-supervised Node Classification.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024

SkipNode: On Alleviating Performance Degradation for Deep Graph Convolutional Networks.

[BibT_eX]

[DOI]

IEEE Trans. Knowl. Data Eng., November, 2024

Aligning Multiple Knowledge Graphs in a Single Pass.

[BibT_eX]

[DOI]

CoRR, 2024

AdaGMLP: AdaBoosting GNN-to-MLP Knowledge Distillation.

[BibT_eX]

[DOI]

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

NodeMixup: Tackling Under-Reaching for Graph Neural Networks.

[BibT_eX]

[DOI]

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

2023

Graph Substructure Assembling Network With Soft Sequence and Context Attention.

[BibT_eX]

[DOI]

IEEE Trans. Knowl. Data Eng., May, 2023

Pseudo Contrastive Learning for Graph-based Semi-supervised Learning.

[BibT_eX]

[DOI]

CoRR, 2023

2022

Self-supervised Heterogeneous Graph Pre-training Based on Structural Clustering.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

SkipNode: On Alleviating Over-smoothing for Deep Graph Convolutional Networks.

[BibT_eX]

[DOI]

CoRR, 2021

Weigang Lu

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