A framework for fully autonomous design of materials via multiobjective optimization and active learning: challenges and next steps

1 code implementation • 15 Apr 2023 • Tyler H. Chang, Jakob R. Elias, Stefan M. Wild, Santanu Chaudhuri, Joseph A. Libera

In order to deploy machine learning in a real-world self-driving laboratory where data acquisition is costly and there are multiple competing design criteria, systems need to be able to intelligently sample while balancing performance trade-offs and constraints.

Active Learning Multiobjective Optimization