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https://github.com/jwsu825/awesome-graph-incremental-learning

This repo contians a list of paper related to graph incremental learning
https://github.com/jwsu825/awesome-graph-incremental-learning

List: awesome-graph-incremental-learning

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This repo contians a list of paper related to graph incremental learning

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# awesome-graph-incremental-learning

- A curated list of up-to-date papers and resources for graph incremental learning, also known as life-long learning and continual learning.

- This Repo is being actively updated and maintained

- Please let us know if we miss any papers!



## Contents

- [Benchmark](#Benchmark)

- [Node-level](#Node-level)

- [Edge-level](#Edge-level)

- [Graph-level](#Graph-level)



## Benchmark



[Graph Lifelong Learning: A Survey](https://ieeexplore-ieee-org.eproxy.lib.hku.hk/abstract/document/10026151) ```IEEE Computational Intelligence Magazine 2023```\

[On Making Graph Continual Learning Easy, Fool-Proof, and Extensive: a Benchmark Framework and Scenarios](https://openreview.net/forum?id=doShL95X0hd) ```ICLR 2023 REJECTED```\

[Continual Graph Learning: A Survey](https://arxiv.org/abs/2301.12230) ```arXiv 2023```\

[CGLB: Benchmark Tasks for Continual Graph Learning](https://papers.nips.cc/paper_files/paper/2022/hash/548a41b9cac6f50dccf7e63e9e1b1b9b-Abstract-Datasets_and_Benchmarks.html) ```Neurips 2022```\

[BeGin: Extensive Benchmark Scenarios and An Easy-to-use Framework for Graph Continual Learning](https://arxiv.org/abs/2211.14568) ```arXiv 2022```



## Node-level

[Towards Robust Graph Incremental Learning on Evolving Graphs](https://icml.cc/virtual/2023/poster/24449) ```ICML 2023```\

[Incremental Causal Graph Learning for Online Root Cause Analysis](https://dl.acm.org/doi/abs/10.1145/3580305.3599392) ```KDD 2023```\

[Data-Free Continual Graph Learning](https://openreview.net/forum?id=RtB4CXS1Jxv) ```ICLR 2023 REJECTED```\

[Self-Supervised Continual Graph Learning in Adaptive Riemannian Spaces](https://ojs.aaai.org/index.php/AAAI/article/view/25586/25358) ```AAAI 2023```\

[Continual Learning on Dynamic Graphs via Parameter Isolation](https://dl.acm.org/doi/abs/10.1145/3539618.3591652) ```SIGIR 2023```\

[Lifelong Graph Learning](https://ieeexplore.ieee.org/document/9880376) ```CVPR 2022```\

[Hierarchical Prototype Networks for Continual Graph Representation Learning](https://ieeexplore.ieee.org/abstract/document/9808404) ```IEEE 2022```\

[Geometer: Graph Few-Shot Class-Incremental Learning via Prototype Representation](https://dl.acm.org/doi/abs/10.1145/3534678.3539280) ```KDD 2022```\

[Streaming Graph Neural Networks with Generative Replay](https://dl.acm.org/doi/10.1145/3534678.3539336) ```KDD 2022```\

[Multimodal Continual Graph Learning with Neural Architecture Search](https://dl.acm.org/doi/10.1145/3485447.3512176) ```WWW 2022```\

[Hierarchical Prototype Networks for Continual Graph Representation Learning](https://ieeexplore.ieee.org/document/9808404) ```TPAMI 2022```\

[Reinforced Continual Learning for Graphs](https://ojs.aaai.org/index.php/AAAI/article/view/25586/25358) ```CIKM 2022```\

[Sparsified Subgraph Memory for Continual Graph Representation Learning](https://ieeexplore.ieee.org/document/10027629) ```ICDM 2022```\

[Continual Learning on Dynamic Graphs via Parameter Isolation](https://ieeexplore.ieee.org/document/10027629) ```ICDM 2022```\

[Learning on streaming graphs with experience replay](https://dl.acm.org/doi/10.1145/3477314.3507113) ```SIGAPP 2022```\

[DyGRAIN: An Incremental Learning Framework for Dynamic Graphs](https://www.ijcai.org/proceedings/2022/0438.pdf) ```IJCAI 2022```\

[Weighted Heterogeneous Graph-Based Incremental Automatic Disease Diagnosis Method](https://link.springer.com/article/10.1007/s12204-022-2537-z) ```Journal of Shanghai Jiaotong University (Science) 2022```\

[Graph Few-shot Class-incremental Learning](https://dl.acm.org/doi/10.1145/3488560.3498455) ```WSDM 2022```\

[Overcoming Catastrophic Forgetting in Graph Neural Networks](https://ojs.aaai.org/index.php/AAAI/article/view/17049/16856) ```AAAI 2021```\

[Lifelong Learning of Graph Neural Networks for Open-World Node Classification](https://ieeexplore.ieee.org/abstract/document/9533412) ```IEEE IJCNN 2021```\

[Continual Learning for Fake News Detection from Social Media](https://dl.acm.org/doi/abs/10.1007/978-3-030-86340-1_30) ```ICANN 2021```\

[Graph-Adaptive Incremental Learning Using an Ensemble of Gaussian Process Experts](https://ieeexplore.ieee.org/document/9413970) ```ICASSP 2021```\

[Incremental face clustering with optimal summary learning via graph convolutional network](https://ieeexplore.ieee.org/abstract/document/9312781) ```Tsinghua Science and Technology 2021```\

[Incremental Learning on Growing Graphs](https://openreview.net/forum?id=nySHNUlKTVw) ```ICLR 2021 REJECTED```\

[Incremental Spatio-Temporal Graph Learning for Online Query-POI Matching](https://dl.acm.org/doi/10.1145/3442381.3449810) ```WWW 2021```\

[Lifelong Learning of Graph Neural Networks for Open-World Node Classification](https://arxiv.org/abs/2006.14422) ```arXiv 2021```\

[Streaming Graph Neural Networks via Continual Learning](https://dl.acm.org/doi/10.1145/3340531.3411963) ```CIKM 2020```\

[Graph Neural Networks with Continual Learning for Fake News Detection from Social Media](https://arxiv.org/abs/2007.03316) ```arXiv 2020```\

[Disentangle-based Continual Graph Representation Learning](https://aclanthology.org/2020.emnlp-main.237/) ```EMNLP 2020```\

[Streaming Graph Neural Networks](https://dl.acm.org/doi/abs/10.1145/3397271.3401092) ```SIGIR 2020```

[Disentangle-based Continual Graph Representation Learning](https://aclanthology.org/2020.emnlp-main.237/) ```EMNLP 2020```



## Edge-level

[IncreGNN: Incremental Graph Neural Network Learning by Considering Node and Parameter Importance](https://dl.acm.org/doi/abs/10.1007/978-3-031-00123-9_59) ```DASFAA 2022```\

[Structure Aware Experience Replay for Incremental Learning in Graph-based Recommender Systems](https://dl.acm.org/doi/10.1145/3459637.3482193) ```CIKM 2021```\

[Incremental Graph Convolutional Network for Collaborative Filtering](https://dl.acm.org/doi/10.1145/3459637.3482354) ```CIKM 2021```\

[I-GCN: Incremental Graph Convolution Network for Conversation Emotion Detection](https://ieeexplore.ieee.org/document/9565365) ```IEEE Transactions on Multimedia 2021```\

[Incremental Learning on Growing Graphs](https://openreview.net/forum?id=nySHNUlKTVw) ```ICLR 2021 REJECTED```\

[FILDNE: A Framework for Incremental Learning of Dynamic Networks Embeddings](https://dl.acm.org/doi/10.1016/j.knosys.2021.107453) ```Knowledge-Based Systems 2021```\

[GraphSAIL: Graph Structure Aware Incremental Learning for Recommender Systems](https://dl.acm.org/doi/10.1145/3340531.3412754) ```CIKM 2020```\

[Streaming Graph Neural Networks](https://dl.acm.org/doi/abs/10.1145/3397271.3401092) ```SIGIR 2020```



## Graph-level

[Two-level Graph Network for Few-Shot Class-Incremental Learning](https://arxiv.org/abs/2303.13862) ```arXiv 2023```\

[Knowledge graph incremental embedding for unseen modalities](https://dl.acm.org/doi/abs/10.1007/s10115-023-01868-9) ```ACM 2023```\

[Multimodal Continual Graph Learning with Neural Architecture Search](https://dl.acm.org/doi/10.1145/3485447.3512176) ```WWW 2022```\

[Continual Learning of Knowledge Graph Embeddings](https://ieeexplore.ieee.org/document/9343669) ```IEEE Robotics and Automation Letters 2021```\

[Overcoming Catastrophic Forgetting in Graph Neural Networks](https://ojs.aaai.org/index.php/AAAI/article/view/17049/16856) ```AAAI 2021```\

[Catastrophic Forgetting in Deep Graph Networks: an Introductory Benchmark for Graph Classification](https://arxiv.org/abs/2103.11750) ```GLB 2021```\

[TrafficStream: A Streaming Traffic Flow Forecasting Framework Based on Graph Neural Networks and Continual Learning](https://www.ijcai.org/proceedings/2021/0498.pdf) ```IJCAI 2021```\

[FILDNE: A Framework for Incremental Learning of Dynamic Networks Embeddings](https://dl.acm.org/doi/10.1016/j.knosys.2021.107453) ```Knowledge-Based Systems 2021```\

[Enriching Translation-Based Knowledge Graph Embeddings Through Continual Learning](https://ieeexplore.ieee.org/document/8486959) ```IEEE 2018```