Zhixia Zeng
Orcid: 0000-0002-7339-9417
According to our database1,
Zhixia Zeng authored at least 16 papers
between 2023 and 2026.
Collaborative distances:
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Bibliography
2026
Toward robust anomaly detection in noisy time series via diffusion-driven denoising and disentanglement.
J. Supercomput., March, 2026
FDEPCA: A Novel Adaptive Nonlinear Feature Extraction Method via Fruit Fly Olfactory Neural Network for IoMT Anomaly Detection.
IEEE J. Biomed. Health Informatics, January, 2026
Knowl. Based Syst., 2026
MSTDF-AD: Modeling spatiotemporal dependency fusion for non-stationary time series anomaly detection.
Inf. Process. Manag., 2026
CSCAD: Modeling cross-scale sequence correlations for multivariate time series anomaly detection.
Inf. Process. Manag., 2026
Neurocomputing, 2026
Unsupervised anomaly detection in energy storage systems using Dual-View latent variable modeling.
Eng. Appl. Artif. Intell., 2026
2025
Knowl. Based Syst., 2025
Semi-supervised anomaly detection via reinforcement learning-enabled method with causal inference.
Inf. Sci., 2025
2024
Graph Autoencoder Anomaly Detection for E-Commerce Application by Contextual Integrating Contrast With Reconstruction and Complementarity.
IEEE Trans. Consumer Electron., February, 2024
RelTrans: An Enhancing Offline Reinforcement Learning Model for the Complex Hand Gesture Decision-Making Task.
IEEE Trans. Consumer Electron., February, 2024
Semi-supervised Anomaly Detection via Adaptive Reinforcement Learning-Enabled Method with Causal Inference for Sensor Signals.
CoRR, 2024
2023
Double locality sensitive hashing Bloom filter for high-dimensional streaming anomaly detection.
Inf. Process. Manag., May, 2023
ITran: A novel transformer-based approach for industrial anomaly detection and localization.
Eng. Appl. Artif. Intell., 2023
Anomaly detection for high-dimensional dynamic data stream using stacked habituation autoencoder and union kernel density estimator.
Concurr. Comput. Pract. Exp., 2023
Proceedings of the 2023 2nd Asia Conference on Algorithms, Computing and Machine Learning, 2023