| A Review of Molecular Representation in the Age of Machine Learning DS Wigh, J Goodman, A Lapkin WIREs Computational Molecular Science, 2022 | 260 | 2022 |
| Accelerated chemical reaction optimization using multi-task learning CJ Taylor, KC Felton, D Wigh, MI Jeraal, R Grainger, G Chessari, ... ACS Central Science 9 (5), 957-968, 2023 | 56 | 2023 |
| Wiley Interdiscip DS Wigh, JM Goodman, AA Lapkin Rev.: Comput. Mol. Sci 12 (5), 2022 | 15 | 2022 |
| Orderly: data sets and benchmarks for chemical reaction data DS Wigh, J Arrowsmith, A Pomberger, KC Felton, AA Lapkin Journal of Chemical Information and Modeling 64 (9), 3790-3798, 2024 | 9 | 2024 |
| Multi-task Bayesian optimization of chemical reactions K Felton, D Wigh, A Lapkin | 8 | 2020 |
| A review of molecular representation in the age of machine learning. WIREs Comput Mol Sci 12: e1603 DS Wigh, JM Goodman, AA Lapkin | 6 | 2022 |
| Quantitative In Silico Prediction of the Rate of Protodeboronation by a Mechanistic Density Functional Theory-Aided Algorithm DS Wigh, M Tissot, P Pasau, JM Goodman, AA Lapkin The Journal of Physical Chemistry A 127 (11), 2628-2636, 2023 | 5 | 2023 |
| A Framework for Biogas Exploitation in Italian Waste Water Treatment Plants. G Oluleye, D Wigh, N Shah, M Napoli, A Hawkes CET Journal-Chemical Engineering Transactions, 2019 | 4 | 2019 |
| Algorithmic Approaches for Context-Informed Reaction Prediction D Wigh | | 2024 |
Alexei LapkinUniversity of CambridgeVerified email at cam.ac.uk
