May 3, 2024 � In this paper, we propose a novel Simplified Transformer with Cross-View Attention for Unsupervised Graph-level Anomaly Detection, namely, CVTGAD.

Sep 17, 2023 � In this paper, we propose a novel Simplified Transformer with Cross-View Attention for Unsupervised Graph-level Anomaly Detection, namely, CVTGAD.

Unsupervised graph-level anomaly detection (UGAD) has received remarkable performance in various critical disciplines, such as chemistry analysis and�...

This is the source code of ECML-PKDD'2023 paper "CVTGAD: Simplified Transformer with Cross-View Attention for Unsupervised Graph-level Anomaly Detection".

ECML PKDD 2023: CVTGAD: Simplified Transformer with Cross-View Attention for Unsupervised Graph-Level Anomaly Detection [Paper][Code]; NeurIPS 2023: Towards�...

In this paper, we propose a novel Simplified Transformer with Cross-View Attention for Unsupervised Graph-level Anomaly Detection, namely, CVTGAD. Anomaly�...

CVTGAD: Simplified Transformer with Cross-View Attention for Unsupervised Graph-Level Anomaly Detection. J Li, Q Xing, Q Wang, Y Chang. Joint European�...

CVTGAD: Simplified Transformer with Cross-View Attention for Unsupervised Graph-level Anomaly Detection. View Code Notebook Code for Similar Papers: Code for�...

CVTGAD: Simplified Transformer with Cross-View Attention for Unsupervised Graph-Level Anomaly Detection. ECML/PKDD (1) 2023: 185-200. [i2]. view. electronic�...

Jul 2, 2024 � CVTGAD [6] similarly incorporates graph contrastive learning principles, utilizing transformer for unsupervised graph anomaly detection and�...