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Found 3 papers, 2 papers with code
Two-Stage Deep Anomaly Detection with Heterogeneous Time Series Data
We introduce a data-driven anomaly detection framework using a manufacturing dataset collected from a factory assembly line.
Time-Series Anomaly Detection with Implicit Neural Representation
Detecting anomalies in multivariate time-series data is essential in many real-world applications.
SiReN: Sign-Aware Recommendation Using Graph Neural Networks
In recent years, many recommender systems using network embedding (NE) such as graph neural networks (GNNs) have been extensively studied in the sense of improving recommendation accuracy.
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