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Bibliographic Details
Main Authors:	Niu, Chaoxi, Pang, Guansong, Chen, Ling
Format:	Preprint
Published:	2023
Subjects:	Machine Learning Social and Information Networks
Online Access:	https://arxiv.org/abs/2301.13340
Tags:	Add Tag No Tags, Be the first to tag this record!

Graph Continual Learning with Debiased Lossless Memory Replay
by: Niu, Chaoxi, et al.
Published: (2024)

Replay-and-Forget-Free Graph Class-Incremental Learning: A Task Profiling and Prompting Approach
by: Niu, Chaoxi, et al.
Published: (2024)

Open-Set Graph Anomaly Detection via Normal Structure Regularisation
by: Wang, Qizhou, et al.
Published: (2023)

AnomalyGFM: Graph Foundation Model for Zero/Few-shot Anomaly Detection
by: Qiao, Hezhe, et al.
Published: (2025)

Boosting Multitask Learning on Graphs through Higher-Order Task Affinities
by: Li, Dongyue, et al.
Published: (2023)

Zero-shot Generalist Graph Anomaly Detection with Unified Neighborhood Prompts
by: Niu, Chaoxi, et al.
Published: (2024)

Diffusion-based Negative Sampling on Graphs for Link Prediction
by: Nguyen, Trung-Kien, et al.
Published: (2024)

Community-Invariant Graph Contrastive Learning
by: Tan, Shiyin, et al.
Published: (2024)

Robust Graph Contrastive Learning with Information Restoration
by: Zhu, Yulin, et al.
Published: (2023)

Homophily-aware Heterogeneous Graph Contrastive Learning
by: Wang, Haosen, et al.
Published: (2025)

Graph Contrastive Invariant Learning from the Causal Perspective
by: Mo, Yanhu, et al.
Published: (2024)

Hypergraph Contrastive Learning for both Homophilic and Heterophilic Hypergraphs
by: Guan, Renchu, et al.
Published: (2025)

Metapath-based Hyperbolic Contrastive Learning for Heterogeneous Graph Embedding
by: Park, Jongmin, et al.
Published: (2025)

Scalable Multitask Learning Using Gradient-based Estimation of Task Affinity
by: Li, Dongyue, et al.
Published: (2024)

Meta-GPS++: Enhancing Graph Meta-Learning with Contrastive Learning and Self-Training
by: Liu, Yonghao, et al.
Published: (2024)

Incorporating Attributes and Multi-Scale Structures for Heterogeneous Graph Contrastive Learning
by: Jiang, Ruobing, et al.
Published: (2025)

Representation Learning for Frequent Subgraph Mining
by: Ying, Rex, et al.
Published: (2024)

The Role of Community Detection Methods in Performance Variations of Graph Mining Tasks
by: Ghosh, Shrabani, et al.
Published: (2025)

GCTAM: Global and Contextual Truncated Affinity Combined Maximization Model For Unsupervised Graph Anomaly Detection
by: Zhang, Xiong, et al.
Published: (2026)

HC-GLAD: Dual Hyperbolic Contrastive Learning for Unsupervised Graph-Level Anomaly Detection
by: Fu, Yali, et al.
Published: (2024)

InfraredGP: Efficient Graph Partitioning via Spectral Graph Neural Networks with Negative Corrections
by: Qin, Meng, et al.
Published: (2025)

Rethinking the Graph Polynomial Filter via Positive and Negative Coupling Analysis
by: Wen, Haodong, et al.
Published: (2024)

Graph Contrastive Learning with Low-Rank Regularization and Low-Rank Attention for Noisy Node Classification
by: Wang, Yancheng, et al.
Published: (2024)

CueGCL: Cluster-aware Personalized Self-Training for Unsupervised Graph Contrastive Learning
by: Li, Yuecheng, et al.
Published: (2023)

Web Scale Graph Mining for Cyber Threat Intelligence
by: Freitas, Scott, et al.
Published: (2024)

Uncertainty Estimation for Heterophilic Graphs Through the Lens of Information Theory
by: Fuchsgruber, Dominik, et al.
Published: (2025)

Subgraph Pooling: Tackling Negative Transfer on Graphs
by: Wang, Zehong, et al.
Published: (2024)

Separated Contrastive Learning for Matching in Cross-domain Recommendation with Curriculum Scheduling
by: Chang, Heng, et al.
Published: (2025)

FTF-ER: Feature-Topology Fusion-Based Experience Replay Method for Continual Graph Learning
by: Pang, Jinhui, et al.
Published: (2024)

Bypassing Skip-Gram Negative Sampling: Dimension Regularization as a More Efficient Alternative for Graph Embeddings
by: Liu, David, et al.
Published: (2024)

DELTA: Dual Consistency Delving with Topological Uncertainty for Active Graph Domain Adaptation
by: Wang, Pengyun, et al.
Published: (2024)

LAMP: Learnable Meta-Path Guided Adversarial Contrastive Learning for Heterogeneous Graphs
by: Li, Siqing, et al.
Published: (2024)

Counterfactual Data Augmentation with Denoising Diffusion for Graph Anomaly Detection
by: Xiao, Chunjing, et al.
Published: (2024)

Explainable Hierarchical Urban Representation Learning for Commuting Flow Prediction
by: Cai, Mingfei, et al.
Published: (2024)

Motif-Consistent Counterfactuals with Adversarial Refinement for Graph-Level Anomaly Detection
by: Xiao, Chunjing, et al.
Published: (2024)

Cluster-guided Contrastive Class-imbalanced Graph Classification
by: Ju, Wei, et al.
Published: (2024)

Graph Machine Learning based Doubly Robust Estimator for Network Causal Effects
by: Khatami, Seyedeh Baharan, et al.
Published: (2024)

Scalable Deep Graph Clustering with Random-walk based Self-supervised Learning
by: Li, Xiang, et al.
Published: (2021)

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