87 citations · 117 across the 5 of their papers we have counts for
4 papers · 1 filter
Temporal Spatial Decomposition and Fusion Network for Time Series Forecasting
Liwang Zhou, Jing Gao
Feature engineering is required to obtain better results for time series forecasting, and decomposition is a crucial one. One decomposition approach often cannot be used for numero…
RobustTAD: Robust Time Series Anomaly Detection via Decomposition and Convolutional Neural Networks
Jingkun Gao, Xiaomin Song, Qingsong Wen +3
The monitoring and management of numerous and diverse time series data at Alibaba Group calls for an effective and scalable time series anomaly detection service. In this paper, we…
RobustTrend: A Huber Loss with a Combined First and Second Order Difference Regularization for Time Series Trend Filtering
Qingsong Wen, Jingkun Gao, Xiaomin Song +2
Extracting the underlying trend signal is a crucial step to facilitate time series analysis like forecasting and anomaly detection. Besides noise signal, time series can contain no…
RobustSTL: A Robust Seasonal-Trend Decomposition Algorithm for Long Time Series
Qingsong Wen, Jingkun Gao, Xiaomin Song +3
Decomposing complex time series into trend, seasonality, and remainder components is an important task to facilitate time series anomaly detection and forecasting. Although numerou…