English(EN) MIGONet: a multiple-input graph neural operator with solver-free discrete manufactured-solution training

MIGONet 推出用于输运现象建模的无求解器训练方法

作者 PulseAugur 编辑部 · [1 个来源] · 2026-11-05 05:00

研究人员推出了一种新颖的图神经网络算子 MIGONet，用于输运现象的代理建模。该模型采用一种独特的训练方法，称为离散制造解 (MMS)，无需求解偏微分方程，从而显著缩短了数据生成时间。在热传导模拟中，MIGONet 的表现优于 MIONet 和其局部版本等现有方法，实现了显著更低的平均相对温度误差。 AI

影响这种新方法显著降低了用于科学模拟的 AI 模型训练数据的计算成本。

排序理由该条目是一篇学术论文，详细介绍了一种用于科学模拟的新方法和模型。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.LG TIER_1 English(EN) · Muhammad Hasnain, N. K. Anand, Arun Srinivasa · 2026-11-05 05:00

MIGONet：一种多输入图神经网络算子，采用无求解器离散制造解训练

arXiv:2611.05876v1 Announce Type: new Abstract: Surrogate modeling of transport requires operators that capture the combined influence of spatially distributed sources and Dirichlet and Neumann boundary conditions, together with training datasets that can be generated at low comp…

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MIGONet：一种多输入图神经网络算子，采用无求解器离散制造解训练

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