| GEOM, energy-annotated molecular conformations for property prediction and molecular generation S Axelrod, R Gomez-Bombarelli Scientific Data 9 (1), 185, 2022 | 300 | 2022 |
| Neural scaling of deep chemical models NC Frey, R Soklaski, S Axelrod, S Samsi, R Gomez-Bombarelli, CW Coley, ... Nature Machine Intelligence 5 (11), 1297-1305, 2023 | 98 | 2023 |
| Active learning accelerates ab initio molecular dynamics on reactive energy surfaces SJ Ang, W Wang, D Schwalbe-Koda, S Axelrod, R Gómez-Bombarelli Chem 7 (3), 738-751, 2021 | 75 | 2021 |
| Learning matter: Materials design with machine learning and atomistic simulations S Axelrod, D Schwalbe-Koda, S Mohapatra, J Damewood, KP Greenman, ... Accounts of Materials Research 3 (3), 343-357, 2022 | 73 | 2022 |
| Bottlebrush polymers with flexible enantiomeric side chains display differential biological properties HVT Nguyen, Y Jiang, S Mohapatra, W Wang, JC Barnes, NJ Oldenhuis, ... Nature Chemistry 14 (1), 85-93, 2022 | 67 | 2022 |
| Excited state non-adiabatic dynamics of large photoswitchable molecules using a chemically transferable machine learning potential S Axelrod, E Shakhnovich, R Gómez-Bombarelli Nature communications 13 (1), 3440, 2022 | 63 | 2022 |
| Temperature-transferable coarse-graining of ionic liquids with dual graph convolutional neural networks J Ruza, W Wang, D Schwalbe-Koda, S Axelrod, WH Harris, ... The Journal of chemical physics 153 (16), 2020 | 56 | 2020 |
| Molecular machine learning with conformer ensembles S Axelrod, R Gomez-Bombarelli Machine Learning: Science and Technology 4 (3), 035025, 2023 | 53 | 2023 |
| Differentiable molecular simulations for control and learning W Wang, S Axelrod, R Gómez-Bombarelli arXiv preprint arXiv:2003.00868, 2020 | 47 | 2020 |
| Synthetic glycomacromolecules of defined valency, absolute configuration, and topology distinguish between human lectins M Hartweg, Y Jiang, G Yilmaz, CM Jarvis, HVT Nguyen, GA Primo, ... JACS Au 1 (10), 1621-1630, 2021 | 37 | 2021 |
| Thermal half-lives of azobenzene derivatives: Virtual screening based on intersystem crossing using a machine learning potential S Axelrod, E Shakhnovich, R Gomez-Bombarelli ACS Central Science 9 (2), 166-176, 2023 | 34 | 2023 |
| Hyperbolic metamaterial nanoresonators make poor single-photon sources S Axelrod, MK Dezfouli, HMK Wong, AS Helmy, S Hughes Physical Review B 95 (15), 155424, 2017 | 22 | 2017 |
| An efficient approach to the quantum dynamics and rates of processes induced by natural incoherent light S Axelrod, P Brumer The Journal of chemical physics 149 (11), 2018 | 18 | 2018 |
| Accurate computation of quantum excited states with neural networks D Pfau, S Axelrod, H Sutterud, I von Glehn, JS Spencer Science 385 (6711), eadn0137, 2024 | 17 | 2024 |
| Multiple time scale open systems: Reaction rates and quantum coherence in model retinal photoisomerization under incoherent excitation S Axelrod, P Brumer The Journal of chemical physics 151 (1), 2019 | 14 | 2019 |
| Learned force fields are ready for ground state catalyst discovery M Schaarschmidt, M Riviere, AM Ganose, JS Spencer, AL Gaunt, ... arXiv preprint arXiv:2209.12466, 2022 | 13 | 2022 |
| Theory of hyperbolic stratified nanostructures for surface-enhanced Raman scattering HMK Wong, MK Dezfouli, S Axelrod, S Hughes, AS Helmy Physical Review B 96 (20), 205112, 2017 | 10 | 2017 |
| Natural quantum Monte Carlo computation of excited states D Pfau, S Axelrod, H Sutterud, I von Glehn, JS Spencer arXiv preprint arXiv:2308.16848, 2023 | 9 | 2023 |
| Energy-aware neural architecture selection and hyperparameter optimization NC Frey, D Zhao, S Axelrod, M Jones, D Bestor, V Gadepally, ... 2022 IEEE International Parallel and Distributed Processing Symposium …, 2022 | 7 | 2022 |
| Mapping the space of photoswitchable ligands and photodruggable proteins with computational modeling S Axelrod, E Shakhnovich, R Gómez-Bombarelli Journal of Chemical Information and Modeling 63 (18), 5794-5802, 2023 | 1 | 2023 |
Rafael Gómez-BombarelliAssociate Professor, MIT DMSEایمیل تأیید شده در mit.edu
