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+ normality λc 10−5 λn 10−5 JVP frequency every minibatch (comm_freq=1) Skip blocks first10AFNO blocks detached Comm

Optimiser AdamW Peak learning rate5×10 −6 Weight decay0 Schedule cosine annealing Epochs50 Batch size2(single-GPU, A10080GB) Loss (one-step) latitude-weighted MSE between ˆXt+1, ERA5 Regulariser latent comm · 2013 · arXiv 8704.4785

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Controlling Transient Amplification Improves Long-horizon Rollouts

cs.LG · 2026-05-09 · conditional · novelty 6.0 · 2 refs

Commutativity regularization mitigates transient error amplification in autoregressive neural simulators by penalizing non-normality and non-commutativity of Jacobians, yielding stable long-horizon rollouts.

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  • Controlling Transient Amplification Improves Long-horizon Rollouts cs.LG · 2026-05-09 · conditional · none · ref 20 · 2 links

    Commutativity regularization mitigates transient error amplification in autoregressive neural simulators by penalizing non-normality and non-commutativity of Jacobians, yielding stable long-horizon rollouts.