Capturing Structure Implicitly from Time-Series having Limited Data

@article{Emaasit2018CapturingSI,
  title={Capturing Structure Implicitly from Time-Series having Limited Data},
  author={Daniel Emaasit and Matthew Johnson},
  journal={CoRR},
  year={2018},
  volume={abs/1803.05867}
}
Scientific fields such as insider-threat detection and highway-safety planning often lack sufficient amounts of time-series data to estimate statistical models for the purpose of scientific discovery. Moreover, the available limited data are quite noisy. This presents a major challenge when estimating time-series models that are robust to overfitting and have wellcalibrated uncertainty estimates. Most of the current literature in these fields involve visualizing the time-series for noticeable… CONTINUE READING
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