1 citations · 1 across the 4 of their papers we have counts for
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Same Graph Cross-Task Transfer in GNNs: Protocols and Predictors
Neelam Akula, Surbhi Kumar, Murat Kantarcioglu +1
Many real-world graphs support multiple predictive tasks over the same underlying structure, creating an opportunity to reuse supervision across node classification (NC) and link p…
Adversarial Graph Neural Network Benchmarks: Towards Practical and Fair Evaluation
Tran Gia Bao Ngo, Zulfikar Alom, Federico Errica +2
Adversarial learning and the robustness of Graph Neural Networks (GNNs) are topics of widespread interest in the machine learning community, as documented by the number of adversar…
EMP: Effective Multidimensional Persistence for Graph Representation Learning
Ignacio Segovia-Dominguez, Yuzhou Chen, Cuneyt G. Akcora +4
Topological data analysis (TDA) is gaining prominence across a wide spectrum of machine learning tasks that spans from manifold learning to graph classification. A pivotal techniqu…