Convolutional embedding of attributed molecular graphs for physical property prediction

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    Benoît Playe, Chloé‐Agathe Azencott, Véronique Stoven · 2018 · PLoS ONE
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    Jonathan A. Fine, Judy Kuan‐Yu Liu, Armen G. Beck, Kawthar Zeyad Alzarieni, Xin Ma, Victoria M. Boulos, Hilkka I. Kenttämaa, Gaurav Chopra · 2020 · Chemical Science
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    Nesreen K. Ahmed, Ryan A. Rossi, Rong Zhou, John Boaz Lee, Xiangnan Kong, Theodore L. Willke, Hoda Eldardiry · 2017 · arXiv (Cornell University)
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    Kevin Yang, Kyle Swanson, Wengong Jin, Connor W. Coley, Philipp Eiden, Hua Gao, Angel Guzmán-Pérez, Timothy Hopper, Brian P. Kelley, Miriam Mathea et al. · 2019 · ChemRxiv
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    Jintai Chen, Yaojun Hu, Mingchen Cai, Yingzhou Lu, Yue Wang, Xu Cao, Miao Lin, Hongxia Xu, Jian Wu, Xiao Cao et al. · 2025 · Scientific Data
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    Seung-Gu Kang, Joseph A. Morrone, Jeffrey K. Weber, Wendy D. Cornell · 2022 · Journal of Chemical Information and Modeling
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