7 citations · 25 across the 6 of their papers we have counts for
4 papers · 1 filter
Gaussian Process Latent Variable Modeling for Few-shot Time Series Forecasting
Yunyao Cheng, Chenjuan Guo, Kaixuan Chen +6
Accurate time series forecasting is crucial for optimizing resource allocation, industrial production, and urban management, particularly with the growth of cyber-physical and IoT…
A Comparative Study on Unsupervised Anomaly Detection for Time Series: Experiments and Analysis
Yan Zhao, Liwei Deng, Xuanhao Chen +7
The continued digitization of societal processes translates into a proliferation of time series data that cover applications such as fraud detection, intrusion detection, and energ…
Uncertainty Quantification for Traffic Forecasting: A Unified Approach
Weizhu Qian, Dalin Zhang, Yan Zhao +2
Uncertainty is an essential consideration for time series forecasting tasks. In this work, we specifically focus on quantifying the uncertainty of traffic forecasting. To achieve t…
Robust and Explainable Autoencoders for Unsupervised Time Series Outlier Detection---Extended Version
Tung Kieu, Bin Yang, Chenjuan Guo +4
Time series data occurs widely, and outlier detection is a fundamental problem in data mining, which has numerous applications. Existing autoencoder-based approaches deliver state-…