English(EN) PYTHIA, a transferable machine learning framework for simultaneous defect and adsorption site optimization

PYTHIA框架使用迁移学习进行材料优化

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-23 04:00

研究人员推出PYTHIA，一个新颖的机器学习框架，旨在优化材料的缺陷和吸附位点等性质。PYTHIA利用基础模型和迁移学习，使用一个复杂的预训练模型，然后通过一个转换器层和用于不确定性量化的斯高斯过程进行微调。这种方法使得该框架即使在数据集有限的情况下也能有效，使其适用于新的和研究不足的材料。该系统已被证明能够有效地识别复杂化学系统中的最佳吸附位点。 AI

影响能够更有效地发现和优化新颖和研究不足的系统的材料。

排序理由该项目是一篇详细介绍新机器学习框架的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

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报道来源 [1]

arXiv cs.LG TIER_1 English(EN) · Ioannis Kouroudis, Zhaosu Gu, Poonam, Leon Muller, Alessio Gagliardi · 2026-10-23 04:00

PYTHIA, a transferable machine learning framework for simultaneous defect and adsorption site optimization

arXiv:2610.31539v1 Announce Type: new Abstract: Machine learning has permeated material optimization, providing high value. Nevertheless, its re- liance on a high number of samples limits its applicability to relatively explored material families. In this paper we extend the appl…

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PYTHIA, a transferable machine learning framework for simultaneous defect and adsorption site optimization

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