傅星珵｜广西师范大学｜学者主页

2026

黎曼几何驱动的图基础模型：突破图同构泛化的新路径

李建欣，傅星珵，孙庆赟

《计算》

2026

Towards LLM-Empowered Knowledge Tracing via LLM-Student Hierarchical Behavior Alignment in Hyperbolic Space

Xingcheng Fu, Sheng-Peng Wang, Yi-Sen Gao, Xianxian Li, Chunpei Li, Qingyun Sun, Dongran Yu

AAAI Conference on Artificial Intelligence

DOI

2026

Rethinking heterophilic graph learning via graph curvature

Jian Wang, Xingcheng Fu, Qingyun Sun, Li-e Wang, Hao Peng, Jiting Li, Xianxian Li, Ming-Lai Shao

Knowledge-Based Systems

DOI

2026

Zero-shot Generalizable Graph Anomaly Detection with Mixture of Riemannian Experts

Xinyu Zhao, Qingyun Sun, Jia-Yi Luo, Xingcheng Fu, Jianxin Li

arXiv.org

DOI

2026

Is Fixing Schema Graphs Necessary? Full-Resolution Graph Structure Learning for Relational Deep Learning

Yi Huang, Qingyu Sun, Jia Li, Xingcheng Fu, Jianxin Li

arXiv.org

DOI

2026

CRITIC-R1: Learning Structured Critics for Retrieval-Augmented Generation

Wen Xiao, Zi-Wei Zhang, Chuanyue Yu, Xingcheng Fu, Qingyu Sun, Runhua Xu, Jianxin Li

arXiv.org

DOI

2026

Retrieving Minimal and Sufficient Reasoning Subgraphs with Graph Foundation Models for Path-aware GraphRAG

Haonan Yuan, Qingyun Sun, Junhua Shi, Ming-Jun Liu, Jiaqi Yuan, Zi-Wei Zhang, Xingcheng Fu, Jian-Xin Li

arXiv.org

DOI

2026

RAG-GFM: Overcoming In-Memory Bottlenecks in Graph Foundation Models via Retrieval-Augmented Generation

Haonan Yuan, Qingyun Sun, Jiachen Tao, Xingcheng Fu, Jianxin Li

The Web Conference

DOI

2026

Privacy Auditing of Multi-Domain Graph Pre-Trained Model Under Membership Inference Attacks

Jiayi Luo, Qingyun Sun, Yuecen Wei, Haonan Yuan, Xingcheng Fu, Jianxin Li

Proceedings of the AAAI Conference on Artificial Intelligence

DOI

2026

Is the Information Bottleneck Robust Enough? Towards Label-Noise Resistant Information Bottleneck Learning

Yi Ting Huang, Qingyun Sun, Yisen Gao, Haonan Yuan, Xingcheng Fu, Jianxin Li

Proceedings of the AAAI Conference on Artificial Intelligence

DOI

2026

SA²GFM: Enhancing Robust Graph Foundation Models with Structure-Aware Semantic Augmentation

Junhua Shi, Qingyun Sun, Haonan Yuan, Xingcheng Fu

Proceedings of the AAAI Conference on Artificial Intelligence

DOI

2026

Towards Effective, Stealthy, and Persistent Backdoor Attacks Targeting Graph Foundation Models

Jiayi Luo, Qingyun Sun, Lingjuan Lyu, Ziwei Zhang, Haonan Yuan, Xingcheng Fu, Jianxin Li

Proceedings of the AAAI Conference on Artificial Intelligence

DOI

2026

2nd Workshop on Frontiers in Graph Machine Learning for the Large Model Era

Qingyun Sun, Ziwei Zhang, Xingcheng Fu, Lingjuan Lyu, Yangqiu Song, Jianxin Li, Philip S. Yu

ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)

DOI

2026

Mitigating Privacy Risks in Graph Condensation from a Hyperbolic Geometry Perspective

Yuecen Wei, Liu Yang, Beining Yang, Qingyun Sun, Hao Peng, Tianyu Wo, Chunming Hu, Xingcheng Fu

ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)

DOI

2026

Towards LLM-Empowered Knowledge Tracing via LLM-Student Hierarchical Behavior Alignment in Hyperbolic Space

Association for Artificial Intelligence 2026, Xingcheng Fu, Yisen Gao, Chunpei Li, Xianxian Li, Qingyun Sun, Shengpeng Wang, Dongran Yu

Underline Science Inc.

DOI

2026

CG-MIA: A Causal Generalization framework for cross-domain graph Membership Inference Attack

Peipei Sui, Liu Yang, Yuecen Wei, Sitong Liu, Minglai Shao, Xingcheng Fu

Knowledge-Based Systems

DOI

2026

DG-Game: Dual-view contrastive heterogeneous graph learning for football tactical event classification

Wensheng Wang, Yudi Huang, Haoran Zhou, Shengpeng Wang, Shuli Zhu, Qingyun Sun, Xingcheng Fu

Pattern Recognition

DOI

2026

A Survey on Foundation Models for Structured Data: Tabular, Time Series, and Graphs

Qingyun Sun, Haonan Yuan, Yi Huang, Ziwei Zhang, Xingcheng Fu, R T. Wang, Haoyi Zhou, Jianxin Li, Jia Wu, Philip S. Yu

IEEE Transactions on Knowledge and Data Engineering

DOI

2026

Graph Diffusion Evolution Model for Multi-Conditional Molecular Generation

Xingcheng Fu, Lingyun Liu, Yisen Gao, Tianyu Chen, Qingyun Sun, Jianxin Li, Xianxian Li

ACM Web Conference (WWW)

DOI

2025

Mitigating Message Imbalance in Fraud Detection with Dual-View Graph Representation Learning

Yudan Song, Yuecen Wei, Yuhang Lu, Qingyun Sun, Minglai Shao, Li-e Wang, Chunming Hu, Xianxian Li, Xingcheng Fu

International Joint Conference on Artificial Intelligence

DOI

2025

Controllable Logical Hypothesis Generation for Abductive Reasoning in Knowledge Graphs

Yi-Sen Gao, Jiaxin Bai, Tianshi ZHENG, Qingyun Sun, Zi-Wei Zhang, Jianxin Li, Yang-Qiu Song, Xingcheng Fu

arXiv.org

DOI

2025

Unifying Deductive and Abductive Reasoning in Knowledge Graphs with Masked Diffusion Model

Yi-Sen Gao, Jiaxin Bai, Yi Huang, Xingcheng Fu, Qingyun Sun, Yang-Qiu Song

The Web Conference

DOI

2025

A comprehensive survey on GNN-based anomaly detection: taxonomy, methods, and the role of large language models

Ziqi Yuan, Qingyun Sun, Hao-Yi Zhou, Ming-Lai Shao, Xingcheng Fu

International Journal of Machine Learning and Cybernetics

DOI

2025

Prompt-based Unifying Inference Attack on Graph Neural Networks

Yuecen Wei, Xingcheng Fu, Lingyun Liu, Qingyun Sun, Hao Peng, Chunming Hu

Proceedings of the AAAI Conference on Artificial Intelligence

DOI

2025

OS-GCL: A One-Shot Learner in Graph Contrastive Learning

Cheng Ji, Chenrui He, Qian Li, Qingyun Sun, Xingcheng Fu, Jianxin Li

International Joint Conference on Artificial Intelligence

DOI

2025

Robust Graph Learning Against Adversarial Evasion Attacks via Prior-Free Diffusion-Based Structure Purification

Jia-Yi Luo, Qingyun Sun, Haonan Yuan, Xingcheng Fu, Jianxin Li

The Web Conference

DOI

2025

GraphMoRE: Mitigating Topological Heterogeneity via Mixture of Riemannian Experts

Zi-Hao Guo, Qingyun Sun, Haonan Yuan, Xingcheng Fu, Min Zhou, Yi-Sen Gao, Jianxin Li

AAAI Conference on Artificial Intelligence

DOI

2025

User preference representation and dual contrastive learning for knowledge-aware recommendation

Ting Wei, Li-e Wang, Xingcheng Fu, Xianxian Li

International Journal of Machine Learning and Cybernetics

DOI

2025

How Much Can Transfer? BRIDGE: Bounded Multi-Domain Graph Foundation Model with Generalization Guarantees

Haonan Yuan, Qingyun Sun, Junhua Shi, Xingcheng Fu, Bryan Hooi, Jianxin Li, Philip S. Yu

International Conference on Machine Learning

2025

GraphKeeper: Graph Domain-Incremental Learning via Knowledge Disentanglement and Preservation

Zihao Guo, Qingyun Sun, Ziwei Zhang, Haonan Yuan, Huiping Zhuang, Xingcheng Fu, Jianxin Li

neural information processing systems

DOI

2025

Galaxy Walker: Geometry-aware VLMs For Galaxy-scale Understanding

Tianyu Chen, Xingcheng Fu, Yi-Sen Gao, Haodong Qian, Yue-Cen Wei, Kun Yan, Hao-Yi Zhou, Jianxin Li

Computer Vision and Pattern Recognition

DOI

2025

Robust Graph Condensation via Classification Complexity Mitigation

Jiayi Luo, Qingyun Sun, Beining Yang, Haonan Yuan, Xingcheng Fu, Yanbiao Ma, Jianxin Li, Philip S. Yu

neural information processing systems

DOI

2025

Toward a Unified Geometry Understanding : Riemannian Diffusion Framework for Graph Generation and Prediction

Yisen Gao, Xingcheng Fu, Qingyun Sun, Jianxin Li, Xianxian Li

neural information processing systems

DOI

2025

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

Jiawen Qin, Haonan Yuan, Qingyun Sun, Lyujin Xu, Jiaqi Yuan, Pengfeng Huang, Zhaonan Wang, Xingcheng Fu, Hao Peng, Jianxin Li, Philip S. Yu

International Conference on Learning Representations

2025

GRAVER: Generative Graph Vocabularies for Robust Graph Foundation Models Fine-tuning

Haonan Yuan, Qingyun Sun, Junhua Shi, Xingcheng Fu, Bryan Hooi, Jianxin Li, Philip S. Yu

neural information processing systems

DOI

2025

DyG-RAG: Dynamic Graph Retrieval-Augmented Generation with Event-Centric Reasoning

Qingyun Sun, Jiaqi Yuan, Shan He, Xiao Guan, Haonan Yuan, Xingcheng Fu, Jianxin Li, Philip S. Yu

arXiv.org

DOI

2025

Evolving Graph Learning for Out-of-Distribution Generalization in Non-Stationary Environments

Qingyun Sun, Jia-Yi Luo, Haonan Yuan, Xingcheng Fu, Hao Peng, Jianxin Li, Philip S. Yu

IEEE Transactions on Pattern Analysis and Machine Intelligence

DOI

2025

Frontiers in Graph Machine Learning for the Large Model Era

Qing-Yun Sun, Zi-Wei Zhang, Xingcheng Fu, Yangqiu Song, Jian-Xin Li, Philip S. Yu

International Conference on Information and Knowledge Management

DOI

2025

An Out-Of-Distribution Membership Inference Attack Approach for Cross-Domain Graph Attacks

Jinyan Wang, Yang Liu, Yuecen Wei, Jiaxuan Si, Chenhao Guo, Qingyun Sun, Xianxian Li, Xingcheng Fu

International Joint Conference on Artificial Intelligence

DOI

2025

ST-GCond: Self-supervised and Transferable Graph Dataset Condensation

Beining Yang, Qingyu Sun, Cheng Ji, Xingcheng Fu, Jianxin Li

International Conference on Learning Representations

2025

Discrete Curvature Graph Information Bottleneck

Xingcheng Fu, Jian Wang, Yisen Gao, Qingyun Sun, Haonan Yuan, Jianxin Li, Xianxian Li

Proceedings of the AAAI Conference on Artificial Intelligence

DOI

2025

Bi-Directional Multi-Scale Graph Dataset Condensation via Information Bottleneck

Xingcheng Fu, Yisen Gao, Beining Yang, Yuxuan Wu, Haodong Qian, Qingyun Sun, Xianxian Li

Proceedings of the AAAI Conference on Artificial Intelligence

DOI

2025

DG-Mamba: Robust and Efficient Dynamic Graph Structure Learning with Selective State Space Models

Haonan Yuan, Qingyun Sun, Zhaonan Wang, Xingcheng Fu, Cheng Ji, Yongjian Wang, Bo Jin, Jianxin Li

Proceedings of the AAAI Conference on Artificial Intelligence

DOI

2025

Leveraging Personalized PageRank and Higher-Order Topological Structures for Heterophily Mitigation in Graph Neural Networks

Yumeng Wang, Zengyi Wo, Wenjun Wang, Xingcheng Fu, Minglai Shao

International Joint Conference on Artificial Intelligence

DOI

2025

SIGMA: A Dual-Agent Reinforcement Learning-OptimizedFramework for Graph Classification

Xinbang Cheng, Haodong Qian, Yisen Gao, Xingcheng Fu, Rongye Shi

DOI

2024

Graph Size-imbalanced Learning with Energy-guided Structural Smoothing

Jiawen Qin, Pengfeng Huang, Qingyun Sun, Cheng Ji, Xingcheng Fu, Jianxin Li

Web Search and Data Mining

DOI

2024

Dynamic Graph Information Bottleneck

Haonan Yuan, Qingyun Sun, Xingcheng Fu, Cheng Ji, Jianxin Li

The Web Conference

DOI

2024

CausalFD: causal invariance-based fraud detection against camouflaged preference

Yudan Song, Yue-Cen Wei, Haonan Yuan, Qingyun Sun, Xingcheng Fu, Li-e Wang, Xianxian Li

International Journal of Machine Learning and Cybernetics

DOI

2024

GC-Bench: An Open and Unified Benchmark for Graph Condensation

Qingyu Sun, Ziying Chen, Beining Yang, Cheng Ji, Xingcheng Fu, Sheng Zhou, Hao Peng, Jianxin Li, Philip S. Yu

Neural Information Processing Systems

DOI

2024

Hyperbolic Geometric Latent Diffusion Model for Graph Generation

Xingcheng Fu, Yi-Sen Gao, Yue-Cen Wei, Qingyun Sun, Hao Peng, Jianxin Li, Xianxian Li

International Conference on Machine Learning

DOI

2024

ReGCL: Rethinking Message Passing in Graph Contrastive Learning

Cheng Ji, Zixuan Huang, Qingyun Sun, Hao Peng, Xingcheng Fu, Qian Li, Jianxin Li

AAAI Conference on Artificial Intelligence

DOI

2024

Poincaré Differential Privacy for Hierarchy-Aware Graph Embedding

Yuecen Wei, Haonan Yuan, Xingcheng Fu, Qingyun Sun, Hao Ming Peng, Xianxian Li, Chunming Hu

Proceedings of the AAAI Conference on Artificial Intelligence

DOI

2023

Unbiased and Efficient Self-Supervised Incremental Contrastive Learning

Cheng Ji, Jianxin Li, Hao Peng, Jia Wu, Xingcheng Fu, Qingyun Sun, Philip S. Yu

Web Search and Data Mining

DOI

2023

Hyperbolic Geometric Graph Representation Learning for Hierarchy-imbalance Node Classification

Xingcheng Fu, Yue-Cen Wei, Qingyun Sun, Haonan Yuan, Jia Wu, Hao Peng, Jianxin Li

The Web Conference

DOI

2023

AIC-GNN: Adversarial information completion for graph neural networks

Quanmin Wei, Jinyan Wang, Xingcheng Fu, Jun Hu, Xianxian Li

Information Sciences

DOI

2023

POINE2: Improving Poincaré Embeddings for Hierarchy-Aware Complex Query Reasoning over Knowledge Graphs

J. Liu, Qian-Ren Mao, Jian-Xin Li, Xingcheng Fu, Zheng Wang

European Conference on Artificial Intelligence

DOI

2023

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

Haonan Yuan, Qingyun Sun, Xingcheng Fu, Zi-Wei Zhang, Cheng Ji, Hao Peng, Jian-Xin Li

Neural Information Processing Systems

DOI

2023

Adaptive curvature exploration geometric graph neural network

Xingcheng Fu, Jianxin Li, Jia Wu, Jiawen Qin, Qingyun Sun, Cheng Ji, Sen-Zhang Wang, Hao Peng, Philip S. Yu

Knowledge and Information Systems

DOI

2023

Does Graph Distillation See Like Vision Dataset Counterpart?

Xingcheng Fu, Cheng Ji, Jianxin Li, Qingyu Sun, Hao Tang, Kai Wang, Beining Yang, Yang You

Advances in Neural Information Processing Systems 36

DOI

2023

Heterogeneous graph neural network with semantic-aware differential privacy guarantees

Yue-Cen Wei, Xingcheng Fu, Dong-Qi Yan, Qingyun Sun, Hao Peng, Jia Wu, Jinyan Wang, Xianxian Li

Knowledge and Information Systems

DOI

2023

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

Cheng Ji, Tao Zhao, Qingyun Sun, Xingcheng Fu, Jianxin Li

Pattern Recognition

DOI

2022

Heterogeneous Graph Neural Network for Privacy-Preserving Recommendation

Yue-Cen Wei, Xingcheng Fu, Qingyun Sun, Hao Peng, Jia Wu, Jinyan Wang, Xianxian Li

Industrial Conference on Data Mining

DOI

2022

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

Qingyun Sun, Jianxin Li, Haonan Yuan, Xingcheng Fu, Hao Peng, Cheng Ji, Qian Li, Philip S. Yu

International Conference on Information and Knowledge Management

DOI

2022

Curvature Graph Generative Adversarial Networks

Jianxin Li, Xingcheng Fu, Qingyun Sun, Cheng Ji, Jiajun Tan, Jia Wu, Hao Peng

The Web Conference

DOI

2022

Self-organization Preserved Graph Structure Learning with Principle of Relevant Information

Qingyun Sun, Jianxin Li, Bei-Ning Yang, Xingcheng Fu, Hao Peng, Philip S. Yu

AAAI Conference on Artificial Intelligence

DOI

2021

ACE-HGNN: Adaptive Curvature Exploration Hyperbolic Graph Neural Network

Xingcheng Fu, Jianxin Li, Jia Wu, Qingyun Sun, Cheng Ji, Sen-Zhang Wang, Jiajun Tan, Hao Peng, Philip S. Yu

Industrial Conference on Data Mining

DOI

2021

Graph Structure Learning with Variational Information Bottleneck

Qingyun Sun, Jianxin Li, Hao Peng, Jia Wu, Xingcheng Fu, Cheng Ji, Philip S. Yu

AAAI Conference on Artificial Intelligence

DOI

2021

A Robust and Generalized Framework for Adversarial Graph Embedding

Jianxin Li, Xingcheng Fu, Shijie Zhu, Hao Peng, Sen-Zhang Wang, Qingyun Sun, Philip S. Yu, Lifang He

IEEE Transactions on Knowledge and Data Engineering

DOI

2019

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

Jinyan Wang, Chen Liu, Xingcheng Fu, Xudong Luo, Xianxian Li

Computers & security

DOI

精选作品

期刊论文

黎曼几何驱动的图基础模型：突破图同构泛化的新路径

Towards LLM-Empowered Knowledge Tracing via LLM-Student Hierarchical Behavior Alignment in Hyperbolic Space

Rethinking heterophilic graph learning via graph curvature

Zero-shot Generalizable Graph Anomaly Detection with Mixture of Riemannian Experts

Is Fixing Schema Graphs Necessary? Full-Resolution Graph Structure Learning for Relational Deep Learning

CRITIC-R1: Learning Structured Critics for Retrieval-Augmented Generation

Retrieving Minimal and Sufficient Reasoning Subgraphs with Graph Foundation Models for Path-aware GraphRAG

RAG-GFM: Overcoming In-Memory Bottlenecks in Graph Foundation Models via Retrieval-Augmented Generation

Privacy Auditing of Multi-Domain Graph Pre-Trained Model Under Membership Inference Attacks

Is the Information Bottleneck Robust Enough? Towards Label-Noise Resistant Information Bottleneck Learning

SA²GFM: Enhancing Robust Graph Foundation Models with Structure-Aware Semantic Augmentation

Towards Effective, Stealthy, and Persistent Backdoor Attacks Targeting Graph Foundation Models

2nd Workshop on Frontiers in Graph Machine Learning for the Large Model Era

Mitigating Privacy Risks in Graph Condensation from a Hyperbolic Geometry Perspective

Towards LLM-Empowered Knowledge Tracing via LLM-Student Hierarchical Behavior Alignment in Hyperbolic Space

CG-MIA: A Causal Generalization framework for cross-domain graph Membership Inference Attack

DG-Game: Dual-view contrastive heterogeneous graph learning for football tactical event classification

A Survey on Foundation Models for Structured Data: Tabular, Time Series, and Graphs

Graph Diffusion Evolution Model for Multi-Conditional Molecular Generation

Mitigating Message Imbalance in Fraud Detection with Dual-View Graph Representation Learning

Controllable Logical Hypothesis Generation for Abductive Reasoning in Knowledge Graphs

Unifying Deductive and Abductive Reasoning in Knowledge Graphs with Masked Diffusion Model

A comprehensive survey on GNN-based anomaly detection: taxonomy, methods, and the role of large language models

Prompt-based Unifying Inference Attack on Graph Neural Networks

OS-GCL: A One-Shot Learner in Graph Contrastive Learning

Robust Graph Learning Against Adversarial Evasion Attacks via Prior-Free Diffusion-Based Structure Purification

GraphMoRE: Mitigating Topological Heterogeneity via Mixture of Riemannian Experts

User preference representation and dual contrastive learning for knowledge-aware recommendation

How Much Can Transfer? BRIDGE: Bounded Multi-Domain Graph Foundation Model with Generalization Guarantees

GraphKeeper: Graph Domain-Incremental Learning via Knowledge Disentanglement and Preservation

Galaxy Walker: Geometry-aware VLMs For Galaxy-scale Understanding

Robust Graph Condensation via Classification Complexity Mitigation

Toward a Unified Geometry Understanding : Riemannian Diffusion Framework for Graph Generation and Prediction

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

GRAVER: Generative Graph Vocabularies for Robust Graph Foundation Models Fine-tuning

DyG-RAG: Dynamic Graph Retrieval-Augmented Generation with Event-Centric Reasoning

Evolving Graph Learning for Out-of-Distribution Generalization in Non-Stationary Environments

Frontiers in Graph Machine Learning for the Large Model Era

An Out-Of-Distribution Membership Inference Attack Approach for Cross-Domain Graph Attacks

ST-GCond: Self-supervised and Transferable Graph Dataset Condensation

Discrete Curvature Graph Information Bottleneck

Bi-Directional Multi-Scale Graph Dataset Condensation via Information Bottleneck

DG-Mamba: Robust and Efficient Dynamic Graph Structure Learning with Selective State Space Models

Leveraging Personalized PageRank and Higher-Order Topological Structures for Heterophily Mitigation in Graph Neural Networks

SIGMA: A Dual-Agent Reinforcement Learning-OptimizedFramework for Graph Classification

Graph Size-imbalanced Learning with Energy-guided Structural Smoothing

Dynamic Graph Information Bottleneck

CausalFD: causal invariance-based fraud detection against camouflaged preference

GC-Bench: An Open and Unified Benchmark for Graph Condensation

Hyperbolic Geometric Latent Diffusion Model for Graph Generation

ReGCL: Rethinking Message Passing in Graph Contrastive Learning

Poincaré Differential Privacy for Hierarchy-Aware Graph Embedding

Unbiased and Efficient Self-Supervised Incremental Contrastive Learning

Hyperbolic Geometric Graph Representation Learning for Hierarchy-imbalance Node Classification

AIC-GNN: Adversarial information completion for graph neural networks

POINE2: Improving Poincaré Embeddings for Hierarchy-Aware Complex Query Reasoning over Knowledge Graphs

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

Adaptive curvature exploration geometric graph neural network

Does Graph Distillation See Like Vision Dataset Counterpart?

Heterogeneous graph neural network with semantic-aware differential privacy guarantees

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

Heterogeneous Graph Neural Network for Privacy-Preserving Recommendation

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

Curvature Graph Generative Adversarial Networks

Self-organization Preserved Graph Structure Learning with Principle of Relevant Information

ACE-HGNN: Adaptive Curvature Exploration Hyperbolic Graph Neural Network

Graph Structure Learning with Variational Information Bottleneck

A Robust and Generalized Framework for Adversarial Graph Embedding

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

研究方向