A benchmark study of machine learning methods for molecular electronic transition: Tree‐based ensemble learning versus graph neural network

Research article (Bulletin of the Korean Chemical Society, 2022) · cited 12× · AI/ML
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A benchmark study of machine learning methods for molecular electronic transition: Tree‐based ensemble learning versus graph neural network

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A benchmark study of machine learning methods for molecular electronic transition: Tree‐based ensemble learning versus graph neural network is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). A benchmark study of machine learning methods for molecular electronic transition: Tree‐based ensemble learning versus graph neural network. Retrieved May 24, 2026, from https://4ort.xyz/entity/a-benchmark-study-of-machine-learning-methods-for-molecular-electronic-transition-treebased-ensemble-learning-versus-gra
MLA “A benchmark study of machine learning methods for molecular electronic transition: Tree‐based ensemble learning versus graph neural network.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/a-benchmark-study-of-machine-learning-methods-for-molecular-electronic-transition-treebased-ensemble-learning-versus-gra.
BibTeX @misc{4ortxyz_a-benchmark-study-of-machine-learning-methods-for-molecular-electronic-transition-treebased-ensemble-learning-versus-gra_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{A benchmark study of machine learning methods for molecular electronic transition: Tree‐based ensemble learning versus graph neural network}}, year = {2026}, url = {https://4ort.xyz/entity/a-benchmark-study-of-machine-learning-methods-for-molecular-electronic-transition-treebased-ensemble-learning-versus-gra}, note = {Accessed: 2026-05-24}}
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