Saved in:
| Main Authors: | Tian, Zonggui, Zhang, Du, Dai, Hong-Ning |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2402.06330 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Continual Graph Learning: A Survey
by: Yuan, Qiao, et al.
Published: (2023)
by: Yuan, Qiao, et al.
Published: (2023)
A Topology-aware Graph Coarsening Framework for Continual Graph Learning
by: Han, Xiaoxue, et al.
Published: (2024)
by: Han, Xiaoxue, et al.
Published: (2024)
Fairness in Graph Learning Augmented with Machine Learning: A Survey
by: Luo, Renqiang, et al.
Published: (2025)
by: Luo, Renqiang, et al.
Published: (2025)
Sparse Orthogonal Parameters Tuning for Continual Learning
by: Ning, Kun-Peng, et al.
Published: (2024)
by: Ning, Kun-Peng, et al.
Published: (2024)
Continual Learning for VLMs: A Survey and Taxonomy Beyond Forgetting
by: Liu, Yuyang, et al.
Published: (2025)
by: Liu, Yuyang, et al.
Published: (2025)
Continual Learning with Pre-Trained Models: A Survey
by: Zhou, Da-Wei, et al.
Published: (2024)
by: Zhou, Da-Wei, et al.
Published: (2024)
Towards Graph Prompt Learning: A Survey and Beyond
by: Long, Qingqing, et al.
Published: (2024)
by: Long, Qingqing, et al.
Published: (2024)
Uncertainty Quantification on Graph Learning: A Survey
by: Chen, Chao, et al.
Published: (2024)
by: Chen, Chao, et al.
Published: (2024)
Counterfactual Learning on Graphs: A Survey
by: Guo, Zhimeng, et al.
Published: (2023)
by: Guo, Zhimeng, et al.
Published: (2023)
Is Parameter Collision Hindering Continual Learning in LLMs?
by: Yang, Shuo, et al.
Published: (2024)
by: Yang, Shuo, et al.
Published: (2024)
Continual Learning for Smart City: A Survey
by: Yang, Li, et al.
Published: (2024)
by: Yang, Li, et al.
Published: (2024)
Negative Metric Learning for Graphs
by: Zhao, Yiyang, et al.
Published: (2025)
by: Zhao, Yiyang, et al.
Published: (2025)
Graph Learning under Distribution Shifts: A Comprehensive Survey on Domain Adaptation, Out-of-distribution, and Continual Learning
by: Wu, Man, et al.
Published: (2024)
by: Wu, Man, et al.
Published: (2024)
Incomplete Graph Learning: A Comprehensive Survey
by: Xia, Riting, et al.
Published: (2025)
by: Xia, Riting, et al.
Published: (2025)
A Survey on Fairness for Machine Learning on Graphs
by: Laclau, Charlotte, et al.
Published: (2022)
by: Laclau, Charlotte, et al.
Published: (2022)
Curriculum Graph Machine Learning: A Survey
by: Li, Haoyang, et al.
Published: (2023)
by: Li, Haoyang, et al.
Published: (2023)
Revisiting Weight Regularization for Low-Rank Continual Learning
by: Zheng, Yaoyue, et al.
Published: (2026)
by: Zheng, Yaoyue, et al.
Published: (2026)
A Survey of Continual Reinforcement Learning
by: Pan, Chaofan, et al.
Published: (2025)
by: Pan, Chaofan, et al.
Published: (2025)
DRIFT: A Benchmark for Task-Free Continual Graph Learning with Continuous Distribution Shifts
by: Sun, Guiquan, et al.
Published: (2026)
by: Sun, Guiquan, et al.
Published: (2026)
A Survey on Graph Condensation
by: Xu, Hongjia, et al.
Published: (2024)
by: Xu, Hongjia, et al.
Published: (2024)
Recent Advances of Multimodal Continual Learning: A Comprehensive Survey
by: Yu, Dianzhi, et al.
Published: (2024)
by: Yu, Dianzhi, et al.
Published: (2024)
Online Continual Graph Learning
by: Donghi, Giovanni, et al.
Published: (2025)
by: Donghi, Giovanni, et al.
Published: (2025)
Data-centric Graph Learning: A Survey
by: Guo, Yuxin, et al.
Published: (2023)
by: Guo, Yuxin, et al.
Published: (2023)
Unleashing the Power of Continual Learning on Non-Centralized Devices: A Survey
by: Li, Yichen, et al.
Published: (2024)
by: Li, Yichen, et al.
Published: (2024)
When Meta-Learning Meets Online and Continual Learning: A Survey
by: Son, Jaehyeon, et al.
Published: (2023)
by: Son, Jaehyeon, et al.
Published: (2023)
Graph Neural Networks for Graphs with Heterophily: A Survey
by: Zheng, Xin, et al.
Published: (2022)
by: Zheng, Xin, et al.
Published: (2022)
Federated Continual Learning via Knowledge Fusion: A Survey
by: Yang, Xin, et al.
Published: (2023)
by: Yang, Xin, et al.
Published: (2023)
Prompt Customization for Continual Learning
by: Dai, Yong, et al.
Published: (2024)
by: Dai, Yong, et al.
Published: (2024)
A Survey on Graph Neural Networks and Graph Transformers in Computer Vision: A Task-Oriented Perspective
by: Chen, Chaoqi, et al.
Published: (2022)
by: Chen, Chaoqi, et al.
Published: (2022)
Efficient and Robust Continual Graph Learning for Graph Classification in Biology
by: Zhang, Ding, et al.
Published: (2024)
by: Zhang, Ding, et al.
Published: (2024)
Quantum Graph Attention Network: A Novel Quantum Multi-Head Attention Mechanism for Graph Learning
by: Ning, An, et al.
Published: (2025)
by: Ning, An, et al.
Published: (2025)
Disentangled Representation Learning for Parametric Partial Differential Equations
by: Liu, Ning, et al.
Published: (2024)
by: Liu, Ning, et al.
Published: (2024)
Exploring Concept Subspace for Self-explainable Text-Attributed Graph Learning
by: Han, Xiaoxue, et al.
Published: (2026)
by: Han, Xiaoxue, et al.
Published: (2026)
GraphMaster: Automated Graph Synthesis via LLM Agents in Data-Limited Environments
by: Du, Enjun, et al.
Published: (2025)
by: Du, Enjun, et al.
Published: (2025)
Continual Learning on Graphs: Challenges, Solutions, and Opportunities
by: Zhang, Xikun, et al.
Published: (2024)
by: Zhang, Xikun, et al.
Published: (2024)
Graph Reinforcement Learning for Power Grids: A Comprehensive Survey
by: Hassouna, Mohamed, et al.
Published: (2024)
by: Hassouna, Mohamed, et al.
Published: (2024)
A Comprehensive Survey on Spectral Clustering with Graph Structure Learning
by: Berahmand, Kamal, et al.
Published: (2025)
by: Berahmand, Kamal, et al.
Published: (2025)
Learning Continuous Face Representation with Explicit Functions
by: Zhang, Liping, et al.
Published: (2021)
by: Zhang, Liping, et al.
Published: (2021)
A Survey of Deep Graph Learning under Distribution Shifts: from Graph Out-of-Distribution Generalization to Adaptation
by: Zhang, Kexin, et al.
Published: (2024)
by: Zhang, Kexin, et al.
Published: (2024)
A Survey of Data-Efficient Graph Learning
by: Ju, Wei, et al.
Published: (2024)
by: Ju, Wei, et al.
Published: (2024)
Similar Items
-
Continual Graph Learning: A Survey
by: Yuan, Qiao, et al.
Published: (2023) -
A Topology-aware Graph Coarsening Framework for Continual Graph Learning
by: Han, Xiaoxue, et al.
Published: (2024) -
Fairness in Graph Learning Augmented with Machine Learning: A Survey
by: Luo, Renqiang, et al.
Published: (2025) -
Sparse Orthogonal Parameters Tuning for Continual Learning
by: Ning, Kun-Peng, et al.
Published: (2024) -
Continual Learning for VLMs: A Survey and Taxonomy Beyond Forgetting
by: Liu, Yuyang, et al.
Published: (2025)