Transformers fail to predict catastrophic collapse in unseen parameter regimes of nonlinear dynamical systems, while reservoir computing reliably succeeds.
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Reservoir observers enhanced by residual calibration and attention substantially raise inference accuracy on chaotic systems, especially in previously worst-case input scenarios.
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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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Reservoir observer enhanced with residual calibration and attention mechanism
Reservoir observers enhanced by residual calibration and attention substantially raise inference accuracy on chaotic systems, especially in previously worst-case input scenarios.