CRC-SGAD: Conformal Risk Control for Supervised Graph Anomaly Detection
Fuente:
arXiv
Guardado en:
| Autores principales: | Bai, Songran, Zheng, Xiaolong, Zeng, Daniel Dajun |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Alleviating Performance Disparity in Adversarial Spatiotemporal Graph Learning Under Zero-Inflated Distribution
por: Bai, Songran, et al.
Publicado: (2025)
por: Bai, Songran, et al.
Publicado: (2025)
Deep Causal Learning: Representation, Discovery and Inference
por: Deng, Zizhen, et al.
Publicado: (2022)
por: Deng, Zizhen, et al.
Publicado: (2022)
Learning Feature Encoder with Synthetic Anomalies for Weakly Supervised Graph Anomaly Detection
por: Zhou, Yingjie, et al.
Publicado: (2026)
por: Zhou, Yingjie, et al.
Publicado: (2026)
Conformal Selective Prediction with General Risk Control
por: Bai, Tian, et al.
Publicado: (2026)
por: Bai, Tian, et al.
Publicado: (2026)
Cluster Aware Graph Anomaly Detection
por: Zheng, Lecheng, et al.
Publicado: (2024)
por: Zheng, Lecheng, et al.
Publicado: (2024)
Conformal Risk Training: End-to-End Optimization of Conformal Risk Control
por: Yeh, Christopher, et al.
Publicado: (2025)
por: Yeh, Christopher, et al.
Publicado: (2025)
Normality Calibration in Semi-supervised Graph Anomaly Detection
por: Zeng, Guolei, et al.
Publicado: (2025)
por: Zeng, Guolei, et al.
Publicado: (2025)
Graph Evidential Learning for Anomaly Detection
por: Wei, Chunyu, et al.
Publicado: (2025)
por: Wei, Chunyu, et al.
Publicado: (2025)
GRASP -- Graph-Based Anomaly Detection Through Self-Supervised Classification
por: Buchta, Robin, et al.
Publicado: (2026)
por: Buchta, Robin, et al.
Publicado: (2026)
Conformal Object Detection by Sequential Risk Control
por: andéol, Léo, et al.
Publicado: (2025)
por: andéol, Léo, et al.
Publicado: (2025)
EAGLE: Contrastive Learning for Efficient Graph Anomaly Detection
por: Ren, Jing, et al.
Publicado: (2025)
por: Ren, Jing, et al.
Publicado: (2025)
Robust Anomaly Detection with Graph Neural Networks using Controllability
por: Wei, Yifan, et al.
Publicado: (2025)
por: Wei, Yifan, et al.
Publicado: (2025)
UMGAD: Unsupervised Multiplex Graph Anomaly Detection
por: Li, Xiang, et al.
Publicado: (2024)
por: Li, Xiang, et al.
Publicado: (2024)
Non-Exchangeable Conformal Risk Control
por: Farinhas, António, et al.
Publicado: (2023)
por: Farinhas, António, et al.
Publicado: (2023)
Cross-Validation Conformal Risk Control
por: Cohen, Kfir M., et al.
Publicado: (2024)
por: Cohen, Kfir M., et al.
Publicado: (2024)
Anytime-Valid Conformal Risk Control
por: Hultberg, Bror, et al.
Publicado: (2026)
por: Hultberg, Bror, et al.
Publicado: (2026)
Towards Automated Self-Supervised Learning for Truly Unsupervised Graph Anomaly Detection
por: Li, Zhong, et al.
Publicado: (2025)
por: Li, Zhong, et al.
Publicado: (2025)
CRoC: Context Refactoring Contrast for Graph Anomaly Detection with Limited Supervision
por: Xie, Siyue, et al.
Publicado: (2025)
por: Xie, Siyue, et al.
Publicado: (2025)
Towards Anomaly-Aware Pre-Training and Fine-Tuning for Graph Anomaly Detection
por: Liu, Yunhui, et al.
Publicado: (2025)
por: Liu, Yunhui, et al.
Publicado: (2025)
Selective Conformal Risk Control
por: Xu, Yunpeng, et al.
Publicado: (2025)
por: Xu, Yunpeng, et al.
Publicado: (2025)
Semi-Supervised Conformal Prediction With Unlabeled Nonconformity Score
por: Zhou, Xuanning, et al.
Publicado: (2025)
por: Zhou, Xuanning, et al.
Publicado: (2025)
Conformal Risk Control for Ordinal Classification
por: Xu, Yunpeng, et al.
Publicado: (2024)
por: Xu, Yunpeng, et al.
Publicado: (2024)
Towards Cross-domain Few-shot Graph Anomaly Detection
por: Chen, Jiazhen, et al.
Publicado: (2024)
por: Chen, Jiazhen, et al.
Publicado: (2024)
Towards Multiple Missing Values-resistant Unsupervised Graph Anomaly Detection
por: Chen, Jiazhen, et al.
Publicado: (2025)
por: Chen, Jiazhen, et al.
Publicado: (2025)
Hyperspectral Anomaly Detection with Self-Supervised Anomaly Prior
por: Liu, Yidan, et al.
Publicado: (2024)
por: Liu, Yidan, et al.
Publicado: (2024)
Anomaly Detection and Classification in Knowledge Graphs
por: Senaratne, Asara, et al.
Publicado: (2024)
por: Senaratne, Asara, et al.
Publicado: (2024)
Contrast to Detect: Dynamic Graph Contrastive Regularization for Unsupervised Anomaly Detection in Multivariate Time Series
por: Pei, Yunhua, et al.
Publicado: (2026)
por: Pei, Yunhua, et al.
Publicado: (2026)
Self-Supervised Iterative Refinement for Anomaly Detection in Industrial Quality Control
por: Aqeel, Muhammad, et al.
Publicado: (2024)
por: Aqeel, Muhammad, et al.
Publicado: (2024)
Conformal Risk Control
por: Angelopoulos, Anastasios N., et al.
Publicado: (2022)
por: Angelopoulos, Anastasios N., et al.
Publicado: (2022)
DeNoise: Learning Robust Graph Representations for Unsupervised Graph-Level Anomaly Detection
por: Chen, Qingfeng, et al.
Publicado: (2025)
por: Chen, Qingfeng, et al.
Publicado: (2025)
Automatically Adaptive Conformal Risk Control
por: Blot, Vincent, et al.
Publicado: (2024)
por: Blot, Vincent, et al.
Publicado: (2024)
Semi-supervised Anomaly Detection with Extremely Limited Labels in Dynamic Graphs
por: Chen, Jiazhen, et al.
Publicado: (2025)
por: Chen, Jiazhen, et al.
Publicado: (2025)
OWLEYE: Zero-Shot Learner for Cross-Domain Graph Data Anomaly Detection
por: Zheng, Lecheng, et al.
Publicado: (2026)
por: Zheng, Lecheng, et al.
Publicado: (2026)
Multi-Normal Prototypes Learning for Weakly Supervised Anomaly Detection
por: Dong, Zhijin, et al.
Publicado: (2024)
por: Dong, Zhijin, et al.
Publicado: (2024)
Weakly Supervised Anomaly Detection via Knowledge-Data Alignment
por: Zhao, Haihong, et al.
Publicado: (2024)
por: Zhao, Haihong, et al.
Publicado: (2024)
FracAug: Fractional Augmentation boost Graph-level Anomaly Detection under Limited Supervision
por: Dong, Xiangyu, et al.
Publicado: (2025)
por: Dong, Xiangyu, et al.
Publicado: (2025)
Aligning Model Properties via Conformal Risk Control
por: Overman, William, et al.
Publicado: (2024)
por: Overman, William, et al.
Publicado: (2024)
Conformal Anomaly Detection in Python: Moving Beyond Heuristic Thresholds with 'nonconform'
por: Hennhöfer, Oliver, et al.
Publicado: (2026)
por: Hennhöfer, Oliver, et al.
Publicado: (2026)
SAFE: Self-Supervised Anomaly Detection Framework for Intrusion Detection
por: Li, Elvin, et al.
Publicado: (2025)
por: Li, Elvin, et al.
Publicado: (2025)
Imbalanced Graph-Level Anomaly Detection via Counterfactual Augmentation and Feature Learning
por: Wang, Zitong, et al.
Publicado: (2024)
por: Wang, Zitong, et al.
Publicado: (2024)
Ejemplares similares
-
Alleviating Performance Disparity in Adversarial Spatiotemporal Graph Learning Under Zero-Inflated Distribution
por: Bai, Songran, et al.
Publicado: (2025) -
Deep Causal Learning: Representation, Discovery and Inference
por: Deng, Zizhen, et al.
Publicado: (2022) -
Learning Feature Encoder with Synthetic Anomalies for Weakly Supervised Graph Anomaly Detection
por: Zhou, Yingjie, et al.
Publicado: (2026) -
Conformal Selective Prediction with General Risk Control
por: Bai, Tian, et al.
Publicado: (2026) -
Cluster Aware Graph Anomaly Detection
por: Zheng, Lecheng, et al.
Publicado: (2024)