Optimal sampling of spatial patterns improves deep learning-based early warning signals of critical transitions

Optimal sampling of spatial patterns improves deep learning-based early warning signals of critical transitions

Complex spatio-temporal systems like lakes, forests and climate systems exhibit alternative stable states. In such systems, as the threshold value of the driver is crossed, the system may experience a sudden (discontinuous) transition or smooth (continuous) transition to an undesired steady state. T...

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Bibliographic Details
Main Authors: Smita Deb, Ekansh Mahendru, Paras Goyal, Vishwesha Guttal, Partha Sharathi Dutta, Narayanan C. Krishnan
Format: Article
Language:English
Published: The Royal Society 2024-06-01
Series:Royal Society Open Science
Subjects:
spatial patterns
catastrophic and non-catastrophic transitions
tipping points
deep learning
early warning indicators
classification
Online Access:https://royalsocietypublishing.org/doi/10.1098/rsos.231767

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https://royalsocietypublishing.org/doi/10.1098/rsos.231767

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