P‐3.2: Molecular characterization and property prediction based on Graph Transformer

SID Symposium Digest of Technical PapersVolume 54, Issue S1 p. 620-620 Poster Session: P-3: Applied Vision P-3.2: Molecular characterization and property prediction based on Graph Transformer Zeshi Wu, Zeshi Wu School of Advanced Manufacturing, Fuzhou University, Quanzhou, Fujian, China, 362200Search for more papers by this authorJianpu Lin, Jianpu Lin School of Advanced Manufacturing, Fuzhou University, Quanzhou, Fujian, China, 362200Search for more papers by this author Zeshi Wu, Zeshi Wu School of Advanced Manufacturing, Fuzhou University, Quanzhou, Fujian, China, 362200Search for more papers by this authorJianpu Lin, Jianpu Lin School of Advanced Manufacturing, Fuzhou University, Quanzhou, Fujian, China, 362200Search for more papers by this author First published: 03 August 2023 https://doi.org/10.1002/sdtp.16368AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinkedInRedditWechat No abstract is available for this article. References 1 Feng W, Xiaochen F, Xiao G, Lei X, Liangxu X, Shan C. Improving de novo molecule generation by embedding LSTM and attention mechanism in CycleGAN, Front Genet 12 (2021) 709500. 2 Weihua H, Bowen L, Joseph G, Marinka Z, Percy L, Vijay P, Jure L. Pre-training graph neural networks. arXiv preprint arXiv:1905.12265, 2019. 3 Ashish V, Noam S, Niki P, Jakob U, Llion J, Aidan N. G, Łukasz K. Attention is all you need. In Advances in neural information processing systems, 5998–6008(2017). Volume54, IssueS1International Conference on Display Technology 2023 (Volume 54, Issue S1)April 2023Pages 620-620 ReferencesRelatedInformation