Xingcheng Fu

Orcid: 0000-0002-4643-8126

According to our database¹, Xingcheng Fu authored at least 22 papers between 2019 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

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Bibliography

2024

IGL-Bench: Establishing the Comprehensive Benchmark for Imbalanced Graph Learning.

[BibT_eX]

[DOI]

CoRR, 2024

Hyperbolic Geometric Latent Diffusion Model for Graph Generation.

[BibT_eX]

[DOI]

CoRR, 2024

Dynamic Graph Information Bottleneck.

[BibT_eX]

[DOI]

Proceedings of the ACM on Web Conference 2024, 2024

Poincaré Differential Privacy for Hierarchy-Aware Graph Embedding.

[BibT_eX]

[DOI]

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

ReGCL: Rethinking Message Passing in Graph Contrastive Learning.

[BibT_eX]

[DOI]

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

2023

A Robust and Generalized Framework for Adversarial Graph Embedding.

[BibT_eX]

[DOI]

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

Higher-order memory guided temporal random walk for dynamic heterogeneous network embedding.

[BibT_eX]

[DOI]

Pattern Recognit., November, 2023

Heterogeneous graph neural network with semantic-aware differential privacy guarantees.

[BibT_eX]

[DOI]

Knowl. Inf. Syst., October, 2023

Adaptive curvature exploration geometric graph neural network.

[BibT_eX]

[DOI]

Knowl. Inf. Syst., May, 2023

AIC-GNN: Adversarial information completion for graph neural networks.

[BibT_eX]

[DOI]

Inf. Sci., May, 2023

Hyperbolic Geometric Graph Representation Learning for Hierarchy-imbalance Node Classification.

[BibT_eX]

[DOI]

Proceedings of the ACM Web Conference 2023, 2023

Unbiased and Efficient Self-Supervised Incremental Contrastive Learning.

[BibT_eX]

[DOI]

Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023

Environment-Aware Dynamic Graph Learning for Out-of-Distribution Generalization.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Does Graph Distillation See Like Vision Dataset Counterpart?

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

POINE<sup>2</sup>: Improving Poincaré Embeddings for Hierarchy-Aware Complex Query Reasoning over Knowledge Graphs.

[BibT_eX]

[DOI]

Proceedings of the ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland, 2023

Self-Organization Preserved Graph Structure Learning with Principle of Relevant Information.

[BibT_eX]

[DOI]

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

2022

Curvature Graph Generative Adversarial Networks.

[BibT_eX]

[DOI]

Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

Heterogeneous Graph Neural Network for Privacy-Preserving Recommendation.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Data Mining, 2022

Position-aware Structure Learning for Graph Topology-imbalance by Relieving Under-reaching and Over-squashing.

[BibT_eX]

[DOI]

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

Graph Structure Learning with Variational Information Bottleneck.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

ACE-HGNN: Adaptive Curvature Exploration Hyperbolic Graph Neural Network.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Data Mining, 2021

2019

A three-phase approach to differentially private crucial patterns mining over data streams.

[BibT_eX]

[DOI]

Comput. Secur., 2019

Xingcheng Fu

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