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20232026
most citedAn Automated Machine Learning Approach for Detecting Anomalous Peak Patterns in Time Series Data from a Research Watershed in the Northeastern United States Critical Zone

6 citations · 8 across the 4 of their papers we have counts for

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2 papers · 1 filter

cs.LG2023★ 1 cited

TransNAS-TSAD: Harnessing Transformers for Multi-Objective Neural Architecture Search in Time Series Anomaly Detection

Ijaz Ul Haq, Byung Suk Lee, Donna M. Rizzo

The surge in real-time data collection across various industries has underscored the need for advanced anomaly detection in both univariate and multivariate time series data. This…

cs.LG2023★ 6 cited

An Automated Machine Learning Approach for Detecting Anomalous Peak Patterns in Time Series Data from a Research Watershed in the Northeastern United States Critical Zone

Ijaz Ul Haq, Byung Suk Lee, Donna M. Rizzo +1

This paper presents an automated machine learning framework designed to assist hydrologists in detecting anomalies in time series data generated by sensors in a research watershed…