Imagen de Portada

CVTGAD: Simplified Transformer with Cross-View Attention for Unsupervised Graph-level Anomaly Detection

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Li, Jindong, Xing, Qianli, Wang, Qi, Chang, Yi
Formato:	Preprint
Publicado:	2024
Materias:	Machine Learning Artificial Intelligence
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

GLADMamba: Unsupervised Graph-Level Anomaly Detection Powered by Selective State Space Model
por: Fu, Yali, et al.
Publicado: (2025)

FANFOLD: Graph Normalizing Flows-driven Asymmetric Network for Unsupervised Graph-Level Anomaly Detection
por: Cao, Rui, et al.
Publicado: (2024)

Unsupervised Graph Anomaly Detection via Multi-Hypersphere Heterophilic Graph Learning
por: Ni, Hang, et al.
Publicado: (2025)

A Simplifying and Learnable Graph Convolutional Attention Network for Unsupervised Knowledge Graphs Alignment
por: Cai, Weishan, et al.
Publicado: (2024)

HC-GLAD: Dual Hyperbolic Contrastive Learning for Unsupervised Graph-Level Anomaly Detection
por: Fu, Yali, et al.
Publicado: (2024)

Guarding Graph Neural Networks for Unsupervised Graph Anomaly Detection
por: Bei, Yuanchen, et al.
Publicado: (2024)

Scalable Context-Aware Graph Attention for Unsupervised Anomaly Detection in Large-Scale Mobile Networks
por: Malacarne, Sara, et al.
Publicado: (2026)

Towards Automated Self-Supervised Learning for Truly Unsupervised Graph Anomaly Detection
por: Li, Zhong, et al.
Publicado: (2025)

GraphLoRA: Structure-Aware Contrastive Low-Rank Adaptation for Cross-Graph Transfer Learning
por: Yang, Zhe-Rui, et al.
Publicado: (2024)

Unsupervised Surrogate Anomaly Detection
por: Klüttermann, Simon, et al.
Publicado: (2025)

DeNoise: Learning Robust Graph Representations for Unsupervised Graph-Level Anomaly Detection
por: Chen, Qingfeng, et al.
Publicado: (2025)

Attention and Autoencoder Hybrid Model for Unsupervised Online Anomaly Detection
por: Najafi, Seyed Amirhossein, et al.
Publicado: (2024)

Rayleigh Quotient Graph Neural Networks for Graph-level Anomaly Detection
por: Dong, Xiangyu, et al.
Publicado: (2023)

AMAD: AutoMasked Attention for Unsupervised Multivariate Time Series Anomaly Detection
por: Huang, Tiange, et al.
Publicado: (2025)

Unsupervised Identification and Replay-based Detection (UIRD) for New Category Anomaly Detection in ECG Signal
por: Shi, Zhangyue, et al.
Publicado: (2025)

Towards Unsupervised Validation of Anomaly-Detection Models
por: Idan, Lihi
Publicado: (2024)

Unsupervised Symbolic Anomaly Detection
por: Hossain, Md Maruf, et al.
Publicado: (2026)

Calibrated One-class Classification for Unsupervised Time Series Anomaly Detection
por: Xu, Hongzuo, et al.
Publicado: (2022)

VecFormer: Towards Efficient and Generalizable Graph Transformer with Graph Token Attention
por: Zhou, Jingbo, et al.
Publicado: (2026)

Balanced Edge Pruning for Graph Anomaly Detection with Noisy Labels
por: Wang, Zhu, et al.
Publicado: (2024)

Deep Autoencoders for Unsupervised Anomaly Detection in Wildfire Prediction
por: Üstek, İrem, et al.
Publicado: (2024)

Multivariate Time-Series Anomaly Detection based on Enhancing Graph Attention Networks with Topological Analysis
por: Liu, Zhe, et al.
Publicado: (2024)

Graph Evidential Learning for Anomaly Detection
por: Wei, Chunyu, et al.
Publicado: (2025)

CNC: Cross-modal Normality Constraint for Unsupervised Multi-class Anomaly Detection
por: Wang, Xiaolei, et al.
Publicado: (2024)

Unsupervised Anomaly Detection for Tabular Data Using Noise Evaluation
por: Dai, Wei, et al.
Publicado: (2024)

Impact of Inaccurate Contamination Ratio on Robust Unsupervised Anomaly Detection
por: Masakuna, Jordan F., et al.
Publicado: (2024)

Unsupervised Anomaly Detection through Mass Repulsing Optimal Transport
por: Montesuma, Eduardo Fernandes, et al.
Publicado: (2025)

TAS-GNN: A Status-Aware Signed Graph Neural Network for Anomaly Detection in Bitcoin Trust Systems
por: Xue, Chang, et al.
Publicado: (2026)

Angel or Devil: Discriminating Hard Samples and Anomaly Contaminations for Unsupervised Time Series Anomaly Detection
por: Zhang, Ruyi, et al.
Publicado: (2024)

Detect by Yourself: Self-Designing Agentic Workflows for Few-Shot Graph Anomaly Detection
por: Huang, Tairan, et al.
Publicado: (2026)

Unsupervised Detection of Spatiotemporal Anomalies in PMU Data Using Transformer-Based BiGAN
por: Hossain, Muhammad Imran, et al.
Publicado: (2025)

Neighbourhood Transformer: Switchable Attention for Monophily-Aware Graph Learning
por: Luo, Yi, et al.
Publicado: (2026)

Enhancing Fairness in Autoencoders for Node-Level Graph Anomaly Detection
por: Wang, Shouju, et al.
Publicado: (2025)

Meta-Learning Based Few-Shot Graph-Level Anomaly Detection
por: Li, Liting, et al.
Publicado: (2025)

FracAug: Fractional Augmentation boost Graph-level Anomaly Detection under Limited Supervision
por: Dong, Xiangyu, et al.
Publicado: (2025)

Erase then Rectify: A Training-Free Parameter Editing Approach for Cost-Effective Graph Unlearning
por: Yang, Zhe-Rui, et al.
Publicado: (2024)

Meta-Transfer Learning Powered Temporal Graph Networks for Cross-City Real Estate Appraisal
por: Zhang, Weijia, et al.
Publicado: (2024)

JTCSE: Joint Tensor-Modulus Constraints and Cross-Attention for Unsupervised Contrastive Learning of Sentence Embeddings
por: Zong, Tianyu, et al.
Publicado: (2025)

Graph Enhanced Trajectory Anomaly Detection
por: Mbuya, Jonathan Kabala, et al.
Publicado: (2025)

Integrating Graph Neural Networks with Scattering Transform for Anomaly Detection
por: Zoubir, Abdeljalil, et al.
Publicado: (2024)