Creation and interpretation of machine learning models for aqueous solubility prediction by Minyi Su, Enric Herrero

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Investigation of multi-input convolutional neural networks for the prediction of particleboard mechanical properties by Shuoye Chen, Shunsuke Sakai, Miyuki Matsuo-Ueda, Kenji Umemura

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Positional embeddings and zero-shot learning using BERT for molecular-property prediction by Medard Edmund Mswahili, JunHa Hwang, Jagath C. Rajapakse, Kyuri Jo, Young-Seob Jeong

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HPGCN: A graph convolutional network-based prediction model for herbal heat/cold properties by Qikai Niu, Jing’ai Wang, Hongtao Li, Lin Tong, Haiyu Xu, Weina Zhang, Ziling Zeng, Sihong Liu, Wenjing Zong, Siqi Zhang, Siwei Tian, Huamin Zhang, Bing Li

Subjects: “…Herbal property prediction…”
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Machine learning techniques for estimating high–temperature mechanical behavior of high strength steels by C. Yazici, F.J. Domínguez-Gutiérrez

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