NoisyGL: A Comprehensive Benchmark for Graph Neural Networks under Label Noise
–Neural Information Processing Systems
Consequently, label noise is common in real-world graph data, negatively impacting GNNs by propagating incorrect information during training. To address this issue, the study of Graph Neural Networks under Label Noise (GLN) has recently gained traction.
Neural Information Processing Systems
Oct-10-2025, 00:44:16 GMT
- Country:
- Asia > China > Zhejiang Province > Ningbo (0.04)
- Genre:
- Research Report > New Finding (1.00)
- Industry:
- Information Technology (1.00)
- Technology: