GraphDE: A Generative Framework for Debiased Learning and Out-of-Distribution Detection on Graphs

Aug-18-2025, 17:29:35 GMT–Neural Information Processing Systems

Despite the remarkable success of graph neural networks (GNNs) for graph representation learning, they are generally built on the (unreliable) i.i.d.

artificial intelligence, data mining, machine learning, (18 more...)

Neural Information Processing Systems

Aug-18-2025, 17:29:35 GMT

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Country:
- Asia > China > Shanghai > Shanghai (0.04)

Genre:
- Research Report > New Finding (0.46)

Technology:
- Information Technology
  - Artificial Intelligence
    - Machine Learning
      - Neural Networks (1.00)
      - Performance Analysis > Accuracy (0.93)
      - Statistical Learning (1.00)
    - Representation & Reasoning (1.00)
  - Data Science > Data Mining (1.00)
  - Information Management (0.94)

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2 ProblemFormulationandRelatedWorks Intypical graph learning problems, givenasetoflabeled graphsDtr ={(Gi,yi)}N

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