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20182021
most citedTime Series Data Augmentation for Deep Learning: A Survey

484 citations · 756 across the 10 of their papers we have counts for

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Showing cs.LGShow all

5 papers · 1 filter

cs.LG2021★ 5 cited

Interest-oriented Universal User Representation via Contrastive Learning

Qinghui Sun, Jie Gu, Bei Yang +5

User representation is essential for providing high-quality commercial services in industry. Universal user representation has received many interests recently, with which we can b…

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.LG2020★ 98 cited

RobustPeriod: Time-Frequency Mining for Robust Multiple Periodicity Detection

Qingsong Wen, Kai He, Liang Sun +3

Periodicity detection is a crucial step in time series tasks, including monitoring and forecasting of metrics in many areas, such as IoT applications and self-driving database mana…

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…