Evaluating Scalable Uncertainty Estimation Methods for DNN-Based Molecular Property Prediction. - Gabriele Scalia; Colin A. Grambow; Barbara Pernici; Yi-Pei Li; William H. Green Jr. (CoRR, 2019)

Evaluating Scalable Uncertainty Estimation Methods for Deep Learning-Based Molecular Property Prediction. - Gabriele Scalia; Colin A. Grambow; Barbara Pernici; Yi-Pei Li; William H. Green Jr. (J. Chem. Inf. Model., 2020)

Explainable uncertainty quantifications for deep learning-based molecular property prediction. - Chu-I Yang; Yi-Pei Li (J. Cheminformatics, 2023)

Enhancing chemical synthesis: a two-stage deep neural network for predicting feasible reaction conditions. - Lung-Yi Chen; Yi-Pei Li (J. Cheminformatics, 2024)

AutoTemplate: enhancing chemical reaction datasets for machine learning applications in organic chemistry. - Lung-Yi Chen; Yi-Pei Li (J. Cheminformatics, 2024)

Enhancing Activation Energy Predictions under Data Constraints Using Graph Neural Networks. - Han-Chung Chang; Ming-Hsuan Tsai; Yi-Pei Li (J. Chem. Inf. Model., 2025)