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cs.LG2024
Joint Selective State Space Model and Detrending for Robust Time Series Anomaly Detection
Junqi Chen, Xu Tan, Sylwan Rahardja +2
Deep learning-based sequence models are extensively employed in Time Series Anomaly Detection (TSAD) tasks due to their effective sequential modeling capabilities. However, the abi…
cs.LG2024
MSS-PAE: Saving Autoencoder-based Outlier Detection from Unexpected Reconstruction
Xu Tan, Jiawei Yang, Junqi Chen +2
AutoEncoders (AEs) are commonly used for machine learning tasks due to their intrinsic learning ability. This unique characteristic can be capitalized for Outlier Detection (OD). H…
cs.LG2024
Weakly-supervised anomaly detection for multimodal data distributions
Xu Tan, Junqi Chen, Sylwan Rahardja +2
Weakly-supervised anomaly detection can outperform existing unsupervised methods with the assistance of a very small number of labeled anomalies, which attracts increasing attentio…