DSLR: Diversity Enhancement and Structure Learning for Rehearsal-based Graph Continual Learning
Author:
Affiliation:
1. KAIST, Daejeon, Republic of Korea
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3589334.3645561
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3. Measuring and Relieving the Over-Smoothing Problem for Graph Neural Networks from the Topological View
4. Yu Chen, Lingfei Wu, and Mohammed Zaki. 2020b. Iterative deep graph learning for graph neural networks: Better and robust node embeddings. Advances in neural information processing systems, Vol. 33 (2020), 19314--19326.
5. Finding Heterophilic Neighbors via Confidence-based Subgraph Matching for Semi-supervised Node Classification
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