Uncertainty Quantification (UQ)

Uncertainty quantification is the process by which a model evaluates how "sure" it is of its prediction. This is key at the deployment of the model since understanding where the model may have lower accuracy is important for selection of candidates for further evaluation as well as understanding what type of dataset augmentation may be useful. 

Publications

• Chen J, Guo K, Liu Z, Isayev O, Zhang X. Uncertainty-Aware Yield Prediction with Multimodal Molecular Features. In Proceedings of the AAAI Conference on Artificial Intelligence 2024 Mar 24 (Vol. 38, No. 8, pp. 8274-8282).