A multi-step neural operator trained with an implicit BDF-based physics residual loss predicts PDE dynamics for longer horizons than data-only baselines in five benchmark systems.
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PMNO: A novel physics guided multi-step neural operator predictor for partial differential equations
A multi-step neural operator trained with an implicit BDF-based physics residual loss predicts PDE dynamics for longer horizons than data-only baselines in five benchmark systems.