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An Equivariant Generative Framework for Molecular Graph-Structure Co-Design
Zaixi Zhang, Qi Liu, Chee-Kong Lee, Chang-Yu Hsieh, Enhong Chen
doi: https://doi.org/10.1101/2023.04.13.536803
Zaixi Zhang
1Anhui Province Key Lab of Big Data Analysis and Application, University of Science and Technology of China, Hefei, Anhui 230026, China
2State Key Laboratory of Cognitive Intelligence, Hefei, Anhui, 230088, China
Qi Liu
1Anhui Province Key Lab of Big Data Analysis and Application, University of Science and Technology of China, Hefei, Anhui 230026, China
2State Key Laboratory of Cognitive Intelligence, Hefei, Anhui, 230088, China
Chee-Kong Lee
3Tencent America, Palo Alto, CA 94306, United States
Chang-Yu Hsieh
4Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, Zhejiang, 310058, China
Enhong Chen
1Anhui Province Key Lab of Big Data Analysis and Application, University of Science and Technology of China, Hefei, Anhui 230026, China
2State Key Laboratory of Cognitive Intelligence, Hefei, Anhui, 230088, China

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Posted April 17, 2023.
An Equivariant Generative Framework for Molecular Graph-Structure Co-Design
Zaixi Zhang, Qi Liu, Chee-Kong Lee, Chang-Yu Hsieh, Enhong Chen
bioRxiv 2023.04.13.536803; doi: https://doi.org/10.1101/2023.04.13.536803
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