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06/27/2022
Measuring and Improving the Use of Graph Information in Graph Neural Networks
Graph neural networks (GNNs) have been widely used for representation le...
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06/15/2022
Pareto Invariant Risk Minimization
Despite the success of invariant risk minimization (IRM) in tackling the...
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02/16/2022
Understanding and Improving Graph Injection Attack by Promoting Unnoticeability
Recently Graph Injection Attack (GIA) emerges as a practical attack scen...
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02/11/2022
Invariance Principle Meets Out-of-Distribution Generalization on Graphs
Despite recent developments in using the invariance principle from causa...
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10/18/2021
Edge Rewiring Goes Neural: Boosting Network Resilience via Policy Gradient
Improving the resilience of a network protects the system from natural d...
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01/27/2021
Improving Graph Representation Learning by Contrastive Regularization
Graph representation learning is an important task with applications in ...
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09/04/2020
Rethinking Graph Regularization For Graph Neural Networks
The graph Laplacian regularization term is usually used in semi-supervis...
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06/08/2020
