Apr 8, 2021 · This paper presented GTA, a new framework for multivariate time series anomaly detection that involves automatically learning a graph structure, graph ...

This paper presented GTA, a new framework for multivariate time series anomaly detection that involves automatically learning a graph structure, graph ...

Our GTA's Transformer architecture is built on top of Informer who won the best paper award of AAAI'21. One may refer to the link to receive more details. Usage.

Sep 26, 2023 · This paper presented GTA, a new framework for multivariate time series anomaly detection that involves automatically learning a graph structure, ...

This study proposes a transformer-based framework for anomaly detection in IoT systems that employs dynamic graph attention to capture the complex correlations.

Sep 7, 2024 · This work proposed a novel framework, namely GTA, for multivariate time series anomaly detection by automatically learning a graph structure ...

Jun 15, 2022 · In this work, we focus on anomaly detection for multivari- ate time series [8] as a copious amount of IoT sensors in many real-life scenarios ...

This paper presented GTA, a new framework for multivariate time series anomaly detection that involves automatically learning a graph structure, graph ...

5 days ago · In response, we propose a novel unsupervised model called LGAT, which can automatically learn graph structures and leverage an enhanced Anomaly ...

Apr 8, 2021 · This work proposed a novel framework, namely GTA, for multivariate time series anomaly detection by automatically learning a graph structure ...