This is the DIRECT capstone project.
Group Members: Xiaoxiao Jia, Jiaxu Qin, Yize Chen
In this project, we propose to take advantage of recent advances in the research of generative models in machine learning area. An automatic machine learning pipeline for designing and generating new molecules will be developed. We will design an efficient way to convert discrete representations of molecules to a multidimensional continuous representation. This method allows us to approximate sampling valid structures from the distribution of input molecules, and to generate new molecules for efficient exploration and optimization through open-ended spaces of chemical compounds. Existing chemical structures will then be learned and used as the knowledge representations for exploring new molecular structures.