English(EN) Performance of Neural Operator Baselines on 'The Well' Dataset

新研究质疑 'The Well' 数据集上的神经算子基准测试

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-28 04:00

一篇新的 arXiv 论文对 'The Well' 数据集上的神经算子模型性能基准测试提出了质疑。作者发现，最初被视为示例性且经过最少调优训练的基线模型，却被当作了决定性的标准。通过在相同约束条件下对 Tucker 分解傅里叶神经算子 (TFNO) 进行有限的超参数搜索，研究人员在大多数任务上取得了显著更好的结果，有时甚至提高了几个数量级。这表明最初的神经算子基线可能无法准确反映架构性能。 AI

影响强调了在物理系统的机器学习代理模型中进行严格评估和调优的必要性。

排序理由该集群包含一篇学术论文，提出了关于模型性能基准测试的新发现。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

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arXiv cs.LG TIER_1 English(EN) · Yash Pincha, Andy Dimnaku, Andrew Chiang, Adarsh Ganeshram, Valentin Duruisseaux, Anima Anandkumar · 2026-10-28 04:00

Neural Operator 基线在 'The Well' 数据集上的表现

arXiv:2610.33967v1 Announce Type: new Abstract: The Well, a 15-terabyte dataset spanning 16 physical simulation domains, provides an extensive benchmark for developing and evaluating machine learning surrogate models for complex physical systems. The baselines released with the b…

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Neural Operator 基线在 'The Well' 数据集上的表现

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