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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 35 / No. 5: AAAI-21 Technical Tracks 5

Overcoming Catastrophic Forgetting in Graph Neural Networks with Experience Replay

February 1, 2023

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Authors

Fan Zhou

University of Electronic Science and Technology of China


Chengtai Cao

University of Electronic Science and Technology of China


DOI:

10.1609/aaai.v35i5.16602


Abstract:

Graph Neural Networks (GNNs) have recently received significant research attention due to their superior performance on a variety of graph-related learning tasks. Most of the current works focus on either static or dynamic graph settings, addressing a single particular task, e.g., node/graph classification, link prediction. In this work, we investigate the question: can GNNs be applied to continuously learning a sequence of tasks? Towards that, we explore the Continual Graph Learning (CGL) paradigm and present the Experience Replay based framework ER-GNN for CGL to alleviate the catastrophic forgetting problem in existing GNNs. ER-GNN stores knowledge from previous tasks as experiences and replays them when learning new tasks to mitigate the catastrophic forgetting issue. We propose three experience node selection strategies: mean of feature, coverage maximization, and influence maximization, to guide the process of selecting experience nodes. Extensive experiments on three benchmark datasets demonstrate the effectiveness of our ER-GNN and shed light on the incremental graph (non-Euclidean) structure learning.

Topics: AAAI

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HOW TO CITE:

Fan Zhou||Chengtai Cao Overcoming Catastrophic Forgetting in Graph Neural Networks with Experience Replay Proceedings of the AAAI Conference on Artificial Intelligence (2021) 4714-4722.

Fan Zhou||Chengtai Cao Overcoming Catastrophic Forgetting in Graph Neural Networks with Experience Replay AAAI 2021, 4714-4722.

Fan Zhou||Chengtai Cao (2021). Overcoming Catastrophic Forgetting in Graph Neural Networks with Experience Replay. Proceedings of the AAAI Conference on Artificial Intelligence, 4714-4722.

Fan Zhou||Chengtai Cao. Overcoming Catastrophic Forgetting in Graph Neural Networks with Experience Replay. Proceedings of the AAAI Conference on Artificial Intelligence 2021 p.4714-4722.

Fan Zhou||Chengtai Cao. 2021. Overcoming Catastrophic Forgetting in Graph Neural Networks with Experience Replay. "Proceedings of the AAAI Conference on Artificial Intelligence". 4714-4722.

Fan Zhou||Chengtai Cao. (2021) "Overcoming Catastrophic Forgetting in Graph Neural Networks with Experience Replay", Proceedings of the AAAI Conference on Artificial Intelligence, p.4714-4722

Fan Zhou||Chengtai Cao, "Overcoming Catastrophic Forgetting in Graph Neural Networks with Experience Replay", AAAI, p.4714-4722, 2021.

Fan Zhou||Chengtai Cao. "Overcoming Catastrophic Forgetting in Graph Neural Networks with Experience Replay". Proceedings of the AAAI Conference on Artificial Intelligence, 2021, p.4714-4722.

Fan Zhou||Chengtai Cao. "Overcoming Catastrophic Forgetting in Graph Neural Networks with Experience Replay". Proceedings of the AAAI Conference on Artificial Intelligence, (2021): 4714-4722.

Fan Zhou||Chengtai Cao. Overcoming Catastrophic Forgetting in Graph Neural Networks with Experience Replay. AAAI[Internet]. 2021[cited 2023]; 4714-4722.


ISSN: 2374-3468


Published by AAAI Press, Palo Alto, California USA
Copyright 2022, Association for the Advancement of
Artificial Intelligence 1900 Embarcadero Road, Suite
101, Palo Alto, California 94303 All Rights Reserved

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