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Learning Timestamp-Level Representations for Time Series with Hierarchical Contrastive Loss.

, , , , , and . CoRR, (2021)

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Learning Timestamp-Level Representations for Time Series with Hierarchical Contrastive Loss., , , , , and . CoRR, (2021)CMMD: Cross-Metric Multi-Dimensional Root Cause Analysis., , , , , , , and . KDD, page 4310-4320. ACM, (2022)TS2Vec: Towards Universal Representation of Time Series., , , , , , and . AAAI, page 8980-8987. AAAI Press, (2022)Spectral Temporal Graph Neural Network for Multivariate Time-series Forecasting, , , , , , , , , and 1 other author(s). (2021)cite arxiv:2103.07719Comment: Accepted by NeurIPS 2020. 20 pages, 7 figures.Time-Series Anomaly Detection Service at Microsoft., , , , , , , , , and . KDD, page 3009-3017. ACM, (2019)Multivariate Time-series Anomaly Detection via Graph Attention Network., , , , , , , , , and . ICDM, page 841-850. IEEE, (2020)Spectral Temporal Graph Neural Network for Multivariate Time-series Forecasting., , , , , , , , , and 1 other author(s). NeurIPS, (2020)Heat-RL: Online Model Selection for Streaming Time-Series Anomaly Detection., , , , , , , , and . CoLLAs, volume 199 of Proceedings of Machine Learning Research, page 767-777. PMLR, (2022)