Transformers fail to predict catastrophic collapse in unseen parameter regimes of nonlinear dynamical systems, while reservoir computing reliably succeeds.
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nlin.CD 2years
2026 2verdicts
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Reservoir computing on NMF-reduced spatiotemporal data predicts tipping times within narrow windows for dynamical systems and CMIP5 climate projections.
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Can Transformers predict system collapse in dynamical systems?
Transformers fail to predict catastrophic collapse in unseen parameter regimes of nonlinear dynamical systems, while reservoir computing reliably succeeds.
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Anticipating tipping in spatiotemporal systems with machine learning
Reservoir computing on NMF-reduced spatiotemporal data predicts tipping times within narrow windows for dynamical systems and CMIP5 climate projections.