AutoPDE maintains an explicit solver strategy through PDE analysis, numerical method selection, and adaptive tuning, achieving 54.5% pass rate on PDE Agent Bench, 14.2 points above the strongest baseline.
arXiv preprint arXiv:2510.25803 , year=
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A new Ms-MoE-IFactFormer neural operator uses time-step routing and scale-specific experts to achieve stable fine-time-step long-horizon predictions of homogeneous isotropic turbulence and channel flow.
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Stable Fine-Time-Step Long-Horizon Turbulence Prediction with a Multi-Stepsize Mixture-of-Experts Neural Operator
A new Ms-MoE-IFactFormer neural operator uses time-step routing and scale-specific experts to achieve stable fine-time-step long-horizon predictions of homogeneous isotropic turbulence and channel flow.