Efficient Chemical Space Exploration Using Active Learning Based on Marginalized Graph Kernel: an Application for Predicting the Thermodynamic Properties of Alkanes with Molecular Simulation

1 code implementation • 1 Sep 2022 • Yan Xiang, Yu-Hang Tang, Zheng Gong, Hongyi Liu, Liang Wu, Guang Lin, Huai Sun

We introduce an explorative active learning (AL) algorithm based on Gaussian process regression and marginalized graph kernel (GPR-MGK) to explore chemical space with minimum cost.

Active Learning GPR +2