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Learning Chemical Intuition: From Molecular Models to Neural Networks

Year: 2025

Type: article

Abstract: This article examines how both chemists and neural networks learn to predict chemical reactivity through different yet complementary frameworks, exploring how to effectively combine human chemical intuition with machine learning.

Source: CHIMIA International Journal for Chemistry

DOI: 10.2533/chimia.2025.174

Author: Magdalena Lederbauer

Institution: ETH Zurich

Language: English

Topic: Machine Learning in Materials Science

Subfield: Materials Chemistry

Field: Materials Science

Domain: Physical Sciences

Open Access status: diamond

OpenAlex ID: W4408816608

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