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20182022
most citedTime Series Data Augmentation for Deep Learning: A Survey

484 citations · 602 across the 7 of their papers we have counts for

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5 papers · 1 filter

cs.LG2022

Robust Time Series Dissimilarity Measure for Outlier Detection and Periodicity Detection

Xiaomin Song, Qingsong Wen, Yan Li +1

Dynamic time warping (DTW) is an effective dissimilarity measure in many time series applications. Despite its popularity, it is prone to noises and outliers, which leads to singul…

cs.LG2020★ 484 cited

Time Series Data Augmentation for Deep Learning: A Survey

Qingsong Wen, Liang Sun, Fan Yang +4

Deep learning performs remarkably well on many time series analysis tasks recently. The superior performance of deep neural networks relies heavily on a large number of training da…

cs.LG2020★ 87 cited

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…

cs.LG2019★ 3 cited

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…

cs.LG2018★ 24 cited

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…