Learning Chemical Intuition: From Molecular Models to Neural Networks

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.

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Publication Details

Journal
CHIMIA International Journal for Chemistry
Published
2025-03-26
DOI
https://doi.org/10.2533/chimia.2025.174
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
0.00
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article

Learning Chemical Intuition: From Molecular Models to Neural Networks

Magdalena Lederbauer
CHIMIA International Journal for Chemistry
Computational Drug Discovery Methods
article

Learning Chemical Intuition: From Molecular Models to Neural Networks

Magdalena Lederbauer
article en

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.

CHIMIA International Journal for ChemistryVol. 79(3)
ETH Zurich (CH)
Openalex Percentile: Top 93%
Computational Drug Discovery Methods
DOIOpen Access PDFOpenAlex
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Learning Chemical Intuition: From Molecular Models to Neural Networks — Magdalena Lederbauer · CHIMIA International Journal for Chemistry (2025) | TGRS Research Map | TGRS