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Arxiv
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Evidential Spectrum-Aware Contrastive Learning for OOD Detection in Dynamic Graphs
- Recent focus on Out-of-distribution (OOD) detection in dynamic graphs for security-sensitive applications.
- Challenges include high bias and variance due to single-point estimation and score homogenization from lack of OOD training data.
- Introduction of EviSEC, an OOD detector using Evidential Spectrum-aware Contrastive Learning on dynamic graphs.
- Utilizes evidential deep learning and spectrum-aware augmentation to improve OOD detection performance.
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