| Predicting infrared spectra with message passing neural networks C McGill, M Forsuelo, Y Guan, WH Green Journal of Chemical Information and Modeling 61 (6), 2594-2609, 2021 | 45 | 2021 |
| Chemprop: A machine learning package for chemical property prediction E Heid, KP Greenman, Y Chung, SC Li, DE Graff, FH Vermeire, H Wu, ... Journal of Chemical Information and Modeling 64 (1), 9-17, 2023 | 38 | 2023 |
| Interchromophore orientation scaffolding by m-terphenyl oxacyclophanes A Mangalum, BP Morgan, JM Hanley, KM Jecen, CJ McGill, ... Chemical communications 46 (28), 5136-5138, 2010 | 22 | 2010 |
| Characterizing uncertainty in machine learning for chemistry E Heid, CJ McGill, FH Vermeire, WH Green Journal of Chemical Information and Modeling 63 (13), 4012-4029, 2023 | 17 | 2023 |
| Autonomous, multiproperty-driven molecular discovery: From predictions to measurements and back BA Koscher, RB Canty, MA McDonald, KP Greenman, CJ McGill, ... Science 382 (6677), eadi1407, 2023 | 16 | 2023 |
| Monosaccharide isomer interconversions become significant at high temperatures CJ McGill, PR Westmoreland The Journal of Physical Chemistry A 123 (1), 120-131, 2018 | 10 | 2018 |
| Effects of surface species and homogeneous reactions on rates and selectivity in ethane oxidation on oxide catalysts Y Liu, CJ McGill, WH Green, P Deshlahra AIChE Journal 67 (12), e17483, 2021 | 5 | 2021 |
| Molecular Carbonyl Insertion as the Homogeneous Catalysis Mechanism for Transesterification of Dimethyl Terephthalate with Ethylene Glycol CJ McGill, PR Westmoreland Industrial & Engineering Chemistry Research 60 (14), 5090-5101, 2021 | 4 | 2021 |
| Transitory Sensitivity in Automatic Chemical Kinetic Mechanism Analysis MS Johnson, CJ McGill, WH Green | 3 | 2024 |
| Computed Elementary Mechanisms of Homogeneous Catalysis by Saccharide-Derived Hydroxyls, Organophosphorus, and Organotin CJ McGill North Carolina State University, 2019 | 1 | 2019 |
| Mechanism Development for the Generation of Furfural in Xylose Pyrolysis CJ McGill, P Westmoreland 2017 AIChE Annual Meeting, 2017 | 1 | 2017 |
| Exploring Machine Learning Models for Predicting Vapor Pressure E Kaplowitz, C McGill 2023 AIChE Annual Meeting, 2023 | | 2023 |
| Predicting Vapor-Liquid Equilibria Using Physic-Inspired Machine Learning Models A Alqallaf, C McGill 2023 AIChE Annual Meeting, 2023 | | 2023 |
| Errors and Uncertainty in Machine Learning Models EC Heid, C McGill, F Vermeire, WH Green, GKH Madsen | | 2023 |
| Chemprop: Machine Learning for Molecular Property Prediction C McGill, E Heid, Y Chung, K Greenman, D Graff, M Liu, C Bilodeau, ... 2022 AIChE Annual Meeting, 2022 | | 2022 |
| Projecting the Effectiveness of Deep Ensembles C McGill, W Green 2022 AIChE Annual Meeting, 2022 | | 2022 |
| Design of an Automatic Platform for Machine-Learning Model Based Molecular Property Optimization M McDonald, B Koscher, R Canty, SK Ha, C Bilodeau, KP Greenman, ... 2022 AIChE Annual Meeting, 2022 | | 2022 |
| Message Passing Neural Networks for Prediction of IR Spectra CJ McGill, M Forsuelo, Y Guan, W Green 2021 AIChE Annual Meeting, 2021 | | 2021 |
| Characterizing Uncertainty and Error in Machine Learning Chemical Property Prediction E Heid, CJ McGill, F Vermeire, W Green 2021 AIChE Annual Meeting, 2021 | | 2021 |
| Machine Learning and Computational Tools for Molecular Properties and Reaction Systems CJ McGill 2021 AIChE Annual Meeting, 2021 | | 2021 |
