Robust Anomaly Detection for Multivariate Data of Spacecraft Through Recurrent Neural Networks and Extreme Value Theory. - Gang Xiang; Ruishi Lin (IEEE Access, 2021)

Research on Long Life Product Prognostics Technology Based on Deep Learning and Statistical Information Fusion. - Nan Yang; Guanghao Ren; Ruishi Lin; Dongpeng Li; Guigang Zhang (WISA, 2023)

Fault Prognostics for Machinery with Multi-Degradation Stage Based on Deep Residual Network and Multi-Task Learning. - Mingxian Wang; Langfu Cui; Jiahe Jiang; Junle Wang; Yang Jin; Gang Xiang; Jianbing Yang; Ruishi Lin (SAFEPROCESS, 2023)

Adaptive Anomaly Detection in Industrial Systems: An EVT-DTS Approach with LSTM Autoencoders. - Bing Yu; Jiakai Xu; Gang Xiang; Ruishi Lin; LiGuo Zhao; Yang Yu 015 (I2MTC, 2024)

Triple Attention: An Integrated Approach for Interpretable Anomaly Detection in Temporal and Association Dimensions. - Bing Yu; Yang Yu 015; Gang Xiang; Ruishi Lin (IEEE Trans. Instrum. Meas., 2024)