English(EN) GenPFN: An In-Context Tabular Foundation Model Approach for Augmenting Small Datasets in Engineering

GenPFN模型增强工程设计小数据集

作者 PulseAugur 编辑部 · [1 个来源] · 2026-11-14 05:00

研究人员开发了GenPFN，一种利用预训练表格基础模型TabPFN来增强工程领域小数据集的新方法。该方法使用一种无需训练的候选生成器，通过插值生成期望的设计，并利用分类器梯度和高斯噪声进行优化。在类别满意度和真实性方面，GenPFN的性能优于SMOTE和VAE等现有方法，显著降低了预测误差，并增加了案例研究中兼容设计的比例。 AI

影响这种方法可以通过提高在有限数据上训练的预测模型的准确性来加速工程设计。

排序理由该集群包含一篇详细介绍新模型和方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

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报道来源 [1]

arXiv cs.AI TIER_1 English(EN) · Noah J. Bagazinski, Cyril Picard, Faez Ahmed · 2026-11-14 05:00

GenPFN：一种用于增强工程领域小数据集的上下文表格基础模型方法

arXiv:2611.14804v1 Announce Type: new Abstract: Costly simulations and experiments limit the data available for engineering design. This paper proposes GenPFN, a training-free candidate generator guided by a pretrained tabular Prior-Data Fitted Network (TabPFN) classifier with fi…

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报道来源 [1]

GenPFN：一种用于增强工程领域小数据集的上下文表格基础模型方法

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