المؤلفون: Di-Fan Liu, Yong-Xin Zhang, Wen-Zhuo Dong, Qi-Kun Feng, Shao-Long Zhong, Zhi-Min Dang

مصطلحات موضوعية: Genetics, Molecular Biology, Cancer, Biological Sciences not elsewhere classified, Mathematical Sciences not elsewhere classified, Chemical Sciences not elsewhere classified, Information Systems not elsewhere classified, transition temperature (<, temperature polymer dielectrics, shot generation process, node attribute matrix, exact likelihood training, driven material informatics, deep learning techniques, invertible normalizing flow, generating molecular graphs, computational material design, two invertible flows, molecular graph structures, based generative model, learned latent space, molecular graph, latent space, invertible transformations, two steps, efficient design, latent distributions, sample vector, promising way, key challenge

Relation: https://figshare.com/articles/journal_contribution/High-Temperature_Polymer_Dielectrics_Designed_Using_an_Invertible_Molecular_Graph_Generative_Model/24769608

الاتاحة: https://doi.org/10.1021/acs.jcim.3c01572.s001
https://figshare.com/articles/journal_contribution/High-Temperature_Polymer_Dielectrics_Designed_Using_an_Invertible_Molecular_Graph_Generative_Model/24769608