Self-supervised learning for time series analysis: Taxonomy, progress, and prospects
Self-supervised learning (SSL) has recently achieved impressive performance on various
time series tasks. The most prominent advantage of SSL is that it reduces the dependence …
time series tasks. The most prominent advantage of SSL is that it reduces the dependence …
Xpert: Empowering incident management with query recommendations via large language models
Large-scale cloud systems play a pivotal role in modern IT infrastructure. However, incidents
occurring within these systems can lead to service disruptions and adversely affect user …
occurring within these systems can lead to service disruptions and adversely affect user …
Ufo: A ui-focused agent for windows os interaction
We introduce UFO, an innovative UI-Focused agent to fulfill user requests tailored to
applications on Windows OS, harnessing the capabilities of GPT-Vision. UFO employs a …
applications on Windows OS, harnessing the capabilities of GPT-Vision. UFO employs a …
TraceDiag: Adaptive, Interpretable, and Efficient Root Cause Analysis on Large-Scale Microservice Systems
Root Cause Analysis (RCA) is becoming increasingly crucial for ensuring the reliability of
microservice systems. However, performing RCA on modern microservice systems can be …
microservice systems. However, performing RCA on modern microservice systems can be …
A survey on diffusion models for time series and spatio-temporal data
The study of time series data is crucial for understanding trends and anomalies over time,
enabling predictive insights across various sectors. Spatio-temporal data, on the other hand …
enabling predictive insights across various sectors. Spatio-temporal data, on the other hand …
Mobile Trajectory Anomaly Detection: Taxonomy, Methodology, Challenges, and Directions
The growing number of cars on city roads has led to an increase in traffic accidents,
highlighting the need for traffic safety measures. Mobile trajectory anomaly detection is an …
highlighting the need for traffic safety measures. Mobile trajectory anomaly detection is an …
Revisiting VAE for Unsupervised Time Series Anomaly Detection: A Frequency Perspective
Time series Anomaly Detection (AD) plays a crucial role for web systems. Various web
systems rely on time series data to monitor and identify anomalies in real time, as well as to …
systems rely on time series data to monitor and identify anomalies in real time, as well as to …
Large language model guided knowledge distillation for time series anomaly detection
Self-supervised methods have gained prominence in time series anomaly detection due to
the scarcity of available annotations. Nevertheless, they typically demand extensive training …
the scarcity of available annotations. Nevertheless, they typically demand extensive training …
DiffTAD: Denoising diffusion probabilistic models for vehicle trajectory anomaly detection
Vehicle trajectory anomaly detection plays an essential role in the fields of traffic video
surveillance, autonomous driving navigation, and taxi fraud detection. Deep generative …
surveillance, autonomous driving navigation, and taxi fraud detection. Deep generative …
Time series anomaly detection using diffusion-based models
Diffusion models have been recently used for anomaly detection (AD) in images. In this
paper we investigate whether they can also be leveraged for AD on multivariate time series …
paper we investigate whether they can also be leveraged for AD on multivariate time series …