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Journal of Cheminformatics|January 24, 2024
Enhancing chemical synthesis: a two-stage deep neural network for predicting feasible reaction conditionsLung-Yi Chen, Yi-Pei LiNature Communications|April 5, 2025
Uncertainty quantification with graph neural networks for efficient molecular designLung-Yi Chen, Yi-Pei LiBeilstein Journal of Organic Chemistry|October 8, 2024
Machine learning-guided strategies for reaction conditions design and optimizationLung-Yi Chen, Yi-Pei LiJournal of Cheminformatics|June 27, 2024
AutoTemplate: enhancing chemical reaction datasets for machine learning applications in organic chemistryLung-Yi Chen, Yi-Pei LiThe Journal of Physical Chemistry. A|October 11, 2022
Deep Learning-Based Increment Theory for Formation Enthalpy PredictionsLung-Yi Chen, Ting-Wei Hsu, Tsai-Chen Hsiung, et al.Journal of Chemical Theory and Computation|June 19, 2025
Exploring Chemical Space with Chemistry-Inspired Dynamic Quantum Circuits in the NISQ EraLung-Yi Chen, Tai-Yue Li, Yi-Pei Li, et al.Journal of Cheminformatics|February 4, 2023
Explainable uncertainty quantifications for deep learning-based molecular property predictionChu-I Yang, Yi-Pei LiJournal of Chemical Theory and Computation|November 28, 2023
Integrating Chemical Information into Reinforcement Learning for Enhanced Molecular Geometry OptimizationYu-Cheng Chang, Yi-Pei LiJournal of Chemical Theory and Computation|January 20, 2021
Learning to Optimize Molecular Geometries Using Reinforcement LearningKabir Ahuja, William H Green, Yi-Pei LiJournal of Chemical Information and Modeling|January 25, 2025
Enhancing Activation Energy Predictions under Data Constraints Using Graph Neural NetworksHan-Chung Chang, Ming-Hsuan Tsai, Yi-Pei LiPageof 4