[R] A benchmarking framework for time-series unsupervised domain adaptation

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  • AdaTime

    [TKDD 2023] AdaTime: A Benchmarking Suite for Domain Adaptation on Time Series Data

  • Our work "AdaTime: A Systematic Evaluation of Domain Adaptation Algorithms on Time Series Data" is now public. We provide a benchmarking framework named "AdaTime" to fairly evaluate Unsupervised domain adaptation (UDA) approaches on time-series data. We find that UDA approaches proposed for visual data can be directly applied to time-series data, and still achieve excellent performance, even better than methods specially proposed for time-series UDA. Se were impressed by the consistently superior performance of "DIRT-T" method on all the datasets. We provide the code publicly on github https://github.com/emadeldeen24/AdaTime

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

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