GADformer: A Transparent Transformer Model for Group Anomaly Detection on Trajectories

arXiv:2303.09841v2 Announce Type: replace
Abstract: Group Anomaly Detection (GAD) identifies unusual pattern in groups where individual members might not be anomalous. This task is of major importance across multiple disciplines, in which also sequences like trajectories can be considered as a group. As groups become more diverse in heterogeneity and size, detecting group anomalies becomes challenging, especially without supervision. Though Recurrent Neural Networks are well established deep sequence models, their performance can decrease with increasing sequence lengths. Hence, this paper …

abstract anomaly anomaly detection arxiv become cs.lg detection diverse importance major multiple pattern transformer transformer model transparent type