BoTier: multi-objective Bayesian optimization with tiered objective structures

Mohammad Haddadnia

doi:10.1039/d5dd00039d

2025-01-01

Mohammad Haddadnia

Leonie Grashoff

Felix Strieth‐Kalthoff *

DOI：10.1039/d5dd00039d

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摘要

En 中文

科学优化问题通常关注于平衡多个相互竞争的目标，这些目标表达了对于实验结果（例如最大化反应产率）和相应输入参数（例如最小化昂贵试剂的使用）的偏好。在实际中，操作和经济方面的考虑往往为这些目标建立层级结构，这必须在样本高效实验规划算法中得到体现。在此，我们介绍BoTier，这是一个能够灵活表示实验结果和输入参数偏好层级的软件库。我们在合成和真实场景的表面上提供了系统性的基准测试，证明了BoTier在多种应用场景中的稳健适用性。重要的是，BoTier以自动微分的方式实现，能够与BoTorch库无缝集成，从而促进其在科学界中的采用。

期刊

Digital Discovery

IF:

5.6

论文数:

997

被引数:

1.7K

机构

Univ Wuppertal

学者数:

142

论文数: 78

被引数: 22

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