Control Flow Operators in PyTorch
Yidi Wu, Thomas Bohnstingl, et al.
ICML 2025
Computer-aided synthesis design, automation, and analytics assisted by machine learning are promising resources in the researcher’s toolkit. Each component may alleviate the chemist from routine tasks, provide valuable insights from data, and enable more informed experimental design. Herein, we highlight selected works in the field and discuss the different approaches and the problems to which they may apply. We emphasize that there are currently few tools with a low barrier of entry for non-experts, which may limit widespread integration into the researcher’s workflow.
Yidi Wu, Thomas Bohnstingl, et al.
ICML 2025
Wojciech Ozga, Do Le Quoc , et al.
IFIP DBSec 2021
Oscar Sainz, Iker García-ferrero, et al.
ACL 2024
Brian Quanz, Wesley Gifford, et al.
INFORMS 2020