ThomasMBury/deep-early-warnings-pnas
Repository to accompany the publication 'Deep learning for early warning signals of tipping points', PNAS (2021)
This project provides tools to analyze time-series data to detect early warning signs of 'tipping points' – sudden, large shifts in complex systems like ecosystems or climate. It takes historical time series measurements (e.g., climate indicators, population sizes) and outputs predictions about the likelihood of an impending critical transition. Researchers and scientists studying complex dynamic systems would use this to anticipate critical shifts.
Use this if you need to reproduce the deep learning methodology for detecting early warning signals of tipping points described in the PNAS publication.
Not ideal if you're looking for a ready-to-use package for applying these techniques to your own data, as that is covered by the 'ewstools' library.
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Nov 28, 2025
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