2 papers
cs.LG2026
GNNs for Time Series Anomaly Detection: An Open-Source Framework and a Critical Evaluation
Federico Bello, Gonzalo Chiarlone, Marcelo Fiori +2
There is growing interest in applying graph-based methods to Time Series Anomaly Detection (TSAD), particularly Graph Neural Networks (GNNs), as they naturally model dependencies a…
cs.LG2025
Towards Foundation Auto-Encoders for Time-Series Anomaly Detection
Gastón García González, Pedro Casas, Emilio Martínez +1
We investigate a novel approach to time-series modeling, inspired by the successes of large pretrained foundation models. We introduce FAE (Foundation Auto-Encoders), a foundation…