Learning Discriminative and Generalizable Anomaly Detector for Dynamic Graph with Limited Supervision
Fuente:
arXiv
Guardado en:
| Autores principales: | Tian, Yuxing, Qi, Yiyan, Mo, Fengran, Zhang, Weixu, Guo, Jian, Nie, Jian-Yun |
|---|---|
| Formato: | Preprint |
| Publicado: |
2026
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
ReAttn: Improving Attention-based Re-ranking via Attention Re-weighting
por: Tian, Yuxing, et al.
Publicado: (2026)
por: Tian, Yuxing, et al.
Publicado: (2026)
Latent Conditional Diffusion-based Data Augmentation for Continuous-Time Dynamic Graph Model
por: Tian, Yuxing, et al.
Publicado: (2024)
por: Tian, Yuxing, et al.
Publicado: (2024)
Learning to Route Queries to Heads for Attention-based Re-ranking with Large Language Models
por: Tian, Yuxing, et al.
Publicado: (2026)
por: Tian, Yuxing, et al.
Publicado: (2026)
Guided Learning: Lubricating End-to-End Modeling for Multi-stage Decision-making
por: Guo, Jian, et al.
Publicado: (2024)
por: Guo, Jian, et al.
Publicado: (2024)
Mixture of Latent Experts Using Tensor Products
por: Su, Zhan, et al.
Publicado: (2024)
por: Su, Zhan, et al.
Publicado: (2024)
A Generalizable Anomaly Detection Method in Dynamic Graphs
por: Yang, Xiao, et al.
Publicado: (2024)
por: Yang, Xiao, et al.
Publicado: (2024)
Angel or Devil: Discriminating Hard Samples and Anomaly Contaminations for Unsupervised Time Series Anomaly Detection
por: Zhang, Ruyi, et al.
Publicado: (2024)
por: Zhang, Ruyi, et al.
Publicado: (2024)
MLLM Is a Strong Reranker: Advancing Multimodal Retrieval-augmented Generation via Knowledge-enhanced Reranking and Noise-injected Training
por: Chen, Zhanpeng, et al.
Publicado: (2024)
por: Chen, Zhanpeng, et al.
Publicado: (2024)
Predicting Large-scale Urban Network Dynamics with Energy-informed Graph Neural Diffusion
por: Nie, Tong, et al.
Publicado: (2025)
por: Nie, Tong, et al.
Publicado: (2025)
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)
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)
Enhancing Graph Self-Supervised Learning with Graph Interplay
por: Zhao, Xinjian, et al.
Publicado: (2024)
por: Zhao, Xinjian, et al.
Publicado: (2024)
Zero-shot Generalizable Graph Anomaly Detection with Mixture of Riemannian Experts
por: Zhao, Xinyu, et al.
Publicado: (2026)
por: Zhao, Xinyu, et al.
Publicado: (2026)
CSPO: Cross-Market Synergistic Stock Price Movement Forecasting with Pseudo-volatility Optimization
por: Lin, Sida, et al.
Publicado: (2025)
por: Lin, Sida, et al.
Publicado: (2025)
Measuring the Impact of Lexical Training Data Coverage on Hallucination Detection in Large Language Models
por: Zhang, Shuo, et al.
Publicado: (2025)
por: Zhang, Shuo, et al.
Publicado: (2025)
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)
Rethinking Spectral Augmentation for Contrast-based Graph Self-Supervised Learning
por: Jian, Xiangru, et al.
Publicado: (2024)
por: Jian, Xiangru, et al.
Publicado: (2024)
TGB-Seq Benchmark: Challenging Temporal GNNs with Complex Sequential Dynamics
por: Yi, Lu, et al.
Publicado: (2025)
por: Yi, Lu, et al.
Publicado: (2025)
PTCL: Pseudo-Label Temporal Curriculum Learning for Label-Limited Dynamic Graph
por: Zhang, Shengtao, et al.
Publicado: (2025)
por: Zhang, Shengtao, et al.
Publicado: (2025)
Distributionally Robust Policy Evaluation and Learning for Continuous Treatment with Observational Data
por: Leung, Cheuk Hang, et al.
Publicado: (2025)
por: Leung, Cheuk Hang, et al.
Publicado: (2025)
NUM2EVENT: Interpretable Event Reasoning from Numerical time-series
por: Feng, Ninghui, et al.
Publicado: (2025)
por: Feng, Ninghui, et al.
Publicado: (2025)
GraphSubDetector: Time Series Subsequence Anomaly Detection via Density-Aware Adaptive Graph Neural Network
por: Chen, Weiqi, et al.
Publicado: (2024)
por: Chen, Weiqi, et al.
Publicado: (2024)
TA-GGAD: Testing-time Adaptive Graph Model for Generalist Graph Anomaly Detection
por: Zhang, Xiong, et al.
Publicado: (2026)
por: Zhang, Xiong, et al.
Publicado: (2026)
MS$^3$D: A RG Flow-Based Regularization for GAN Training with Limited Data
por: Wang, Jian, et al.
Publicado: (2024)
por: Wang, Jian, et al.
Publicado: (2024)
Towards Generalizable PDE Dynamics Forecasting via Physics-Guided Invariant Learning
por: Li, Siyang, et al.
Publicado: (2025)
por: Li, Siyang, et al.
Publicado: (2025)
BECAUSE: Bilinear Causal Representation for Generalizable Offline Model-based Reinforcement Learning
por: Lin, Haohong, et al.
Publicado: (2024)
por: Lin, Haohong, et al.
Publicado: (2024)
Semantic-based Distributed Learning for Diverse and Discriminative Representations
por: Tian, Zhuojun, et al.
Publicado: (2026)
por: Tian, Zhuojun, et al.
Publicado: (2026)
Graph Evidential Learning for Anomaly Detection
por: Wei, Chunyu, et al.
Publicado: (2025)
por: Wei, Chunyu, et al.
Publicado: (2025)
Can LLMs Serve As Time Series Anomaly Detectors?
por: Dong, Manqing, et al.
Publicado: (2024)
por: Dong, Manqing, et al.
Publicado: (2024)
SCL-GNN: Towards Generalizable Graph Neural Networks via Spurious Correlation Learning
por: Zhang, Yuxiang, et al.
Publicado: (2026)
por: Zhang, Yuxiang, et al.
Publicado: (2026)
LogFormer: A Pre-train and Tuning Pipeline for Log Anomaly Detection
por: Guo, Hongcheng, et al.
Publicado: (2024)
por: Guo, Hongcheng, et al.
Publicado: (2024)
Anomaly Detection in Dynamic Graphs: A Comprehensive Survey
por: Ekle, Ocheme Anthony, et al.
Publicado: (2024)
por: Ekle, Ocheme Anthony, et al.
Publicado: (2024)
On the Implicit Adversariality of Catastrophic Forgetting in Deep Continual Learning
por: Peng, Ze, et al.
Publicado: (2025)
por: Peng, Ze, et al.
Publicado: (2025)
GOPT: Generalizable Online 3D Bin Packing via Transformer-based Deep Reinforcement Learning
por: Xiong, Heng, et al.
Publicado: (2024)
por: Xiong, Heng, et al.
Publicado: (2024)
Reinforcement Learning-Guided Semi-Supervised Learning
por: Heidari, Marzi, et al.
Publicado: (2024)
por: Heidari, Marzi, et al.
Publicado: (2024)
Adaptive Spatiotemporal Augmentation for Improving Dynamic Graph Learning
por: Chu, Xu, et al.
Publicado: (2025)
por: Chu, Xu, et al.
Publicado: (2025)
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)
DiffGAD: A Diffusion-based Unsupervised Graph Anomaly Detector
por: Li, Jinghan, et al.
Publicado: (2024)
por: Li, Jinghan, et al.
Publicado: (2024)
Balanced Direction from Multifarious Choices: Arithmetic Meta-Learning for Domain Generalization
por: Wang, Xiran, et al.
Publicado: (2025)
por: Wang, Xiran, et al.
Publicado: (2025)
DDGAD: Trajectory Dynamics for Diffusion-Based Graph Anomaly Detection
por: Yang, Yuxin, et al.
Publicado: (2026)
por: Yang, Yuxin, et al.
Publicado: (2026)
Ejemplares similares
-
ReAttn: Improving Attention-based Re-ranking via Attention Re-weighting
por: Tian, Yuxing, et al.
Publicado: (2026) -
Latent Conditional Diffusion-based Data Augmentation for Continuous-Time Dynamic Graph Model
por: Tian, Yuxing, et al.
Publicado: (2024) -
Learning to Route Queries to Heads for Attention-based Re-ranking with Large Language Models
por: Tian, Yuxing, et al.
Publicado: (2026) -
Guided Learning: Lubricating End-to-End Modeling for Multi-stage Decision-making
por: Guo, Jian, et al.
Publicado: (2024) -
Mixture of Latent Experts Using Tensor Products
por: Su, Zhan, et al.
Publicado: (2024)