Häse, Florian

Next-Generation Experimentation with Self-Driving Laboratories

Häse, F., Roch, L. M., & Aspuru-Guzik, A. (2019) · Trends in Chemistry

Machine Learning in Materials ScienceArtificial Intelligence Applications

Cited by 426

Phoenics: A Bayesian Optimizer for Chemistry

Häse, F., Roch, L. M., Kreisbeck, C., & Aspuru-Guzik, A. (2018) · ACS Central Science

Optimal Experimental Design MethodsMachine Learning in Materials Science

Cited by 379

Chimera: enabling hierarchy based multi-objective optimization for self-driving laboratories

Häse, F., Roch, L. M., & Aspuru-Guzik, A. (2018) · Chemical Science

Advanced Multi-Objective Optimization AlgorithmsMachine Learning in Materials Science

Cited by 161

Bayesian optimization with known experimental and design constraints for chemistry applications

Hickman, R. J., Aldeghi, M., Häse, F., & Aspuru-Guzik, A. (2022) · Digital Discovery

Optimal Experimental Design MethodsMachine Learning in Materials Science

Cited by 98