AI RESEARCH
A comparative study of accuracy and rollout stability of temporal surrogate models
arXiv CS.LG
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ArXi:2605.24868v1 Announce Type: new Temporal surrogate models are effective for predicting chaotic dynamical systems where computational cost can be prohibitive. Several deep neural network architectures can be used for such purposes. In this work, a few commonly used architectures are compared using a common