Multivariate Time Series Forecasting Based on Causal Inference with Transfer Entropy and Graph Neural Network. - Haoyan Xu; Yida Huang; Ziheng Duan; Jie Feng 006; Pengyu Song (CoRR, 2020)

Parallel Extraction of Long-term Trends and Short-term Fluctuation Framework for Multivariate Time Series Forecasting. - Haoyan Xu; Ziheng Duan; Yida Huang; Jie Feng 006; Anni Ren; Qianru Zhang; Pengyu Song; Xiaoqian Wang 001 (CoRR, 2020)

SFNet: A slow feature extraction network for parallel linear and nonlinear dynamic process monitoring. - Pengyu Song; Chunhui Zhao 001; Biao Huang 001 (Neurocomputing, 2022)

Sparse and Time-Varying Predictive Relation Extraction for Root Cause Quantification of Nonstationary Process Faults. - Pengyu Song; Chunhui Zhao 001; Biao Huang 001; Min Wu 002 (IEEE Trans. Instrum. Meas., 2022)

Spatiotemporal Multiscale Correlation Embedding With Process Variable Reorder for Industrial Soft Sensing. - Jiawei Chen 007; Pengyu Song; Chunhui Zhao 001; Jinliang Ding (IEEE Trans. Instrum. Meas., 2023)

MPGE and RootRank: A sufficient root cause characterization and quantification framework for industrial process faults. - Pengyu Song; Chunhui Zhao 001; Biao Huang 001 (Neural Networks, 2023)

Optimization of Machine Vision Dynamic Monitoring System Based on Deep Learning Algorithms. - Yuan Wang 022; Lei Chen; Jiacheng Nie; Wenkai Ma; Pengyu Song; Di Mei (IoTML, 2024)

Fusing consensus knowledge: A federated learning method for fault diagnosis via privacy-preserving reference under domain shift. - Baoxue Li; Pengyu Song; Chunhui Zhao 001 (Inf. Fusion, 2024)

Facing spatiotemporal heterogeneity: A unified federated continual learning framework with self-challenge rehearsal for industrial monitoring tasks. - Baoxue Li; Pengyu Song; Chunhui Zhao 001; Min Xie 001 (Knowl. Based Syst., 2024)

Towards consensual representation: Model-agnostic knowledge extraction for dual heterogeneous federated fault diagnosis. - Jiaye Wang; Pengyu Song; Chunhui Zhao 001 (Neural Networks, 2024)

Multimodal Decoupled Representation With Compatibility Learning for Explicit Nonstationary Process Monitoring. - Pengyu Song; Chunhui Zhao 001; Jinliang Ding; Shunyi Zhao (IEEE Trans. Ind. Electron., 2024)

Multi-scale self-supervised representation learning with temporal alignment for multi-rate time series modeling. - Jiawei Chen 007; Pengyu Song; Chunhui Zhao 001 (Pattern Recognit., 2024)

Slow Down to Go Better: A Survey on Slow Feature Analysis. - Pengyu Song; Chunhui Zhao 001 (IEEE Trans. Neural Networks Learn. Syst., 2024)

Explicit Representation and Customized Fault Isolation Framework for Learning Temporal and Spatial Dependencies in Industrial Processes. - Pengyu Song; Chunhui Zhao 001; Biao Huang 001; Jinliang Ding (IEEE Trans. Neural Networks Learn. Syst., 2024)

Structure Feature Extraction for Hierarchical Alarm Flood Classification and Alarm Prediction. - Chang Tian; Pengyu Song; Chunhui Zhao 001; Jinliang Ding (IEEE Trans Autom. Sci. Eng., 2024)

Hybrid Probabilistic Slow Feature Analysis of Continuous and Binary Data for Dynamic Process Monitoring. - Junhao Chen; Pengyu Song; Chunhui Zhao 001; Min Xie 001 (IEEE Trans. Syst. Man Cybern. Syst., 2024)

From Static and Dynamic Perspectives: A Survey on Historical Data Benchmarks of Control Performance Monitoring. - Pengyu Song; Jie Wang 063; Chunhui Zhao 001; Biao Huang 001 (IEEE CAA J. Autom. Sinica, 2025)

Unified Low-Dimensional Subspace Analysis of Continuous and Binary Variables for Industrial Process Monitoring. - Junhao Chen; Chunhui Zhao 001; Pengyu Song; Min Xie 001 (IEEE Trans. Cybern., 2025)

Addressing Heterogeneous Time-Frequency Causality: Source Consistency Exploring for Industrial Root Cause Alignment and Diagnosis. - Pengyu Song; Chunhui Zhao 001; Biao Huang 001 (IEEE Trans. Cybern., 2025)

Fuzzy State-Driven Cross-Time Spatial Dependence Learning for Multivariate Time-Series Anomaly Detection. - Kun Zhu 008; Pengyu Song; Chunhui Zhao 001 (IEEE Trans. Neural Networks Learn. Syst., 2025)