| ANI-1: an extensible neural network potential with DFT accuracy at force field computational cost JS Smith, O Isayev, AE Roitberg Chemical Science 8 (4), 3192-3203, 2017 | 1597 | 2017 |
| Less is more: Sampling chemical space with active learning JS Smith, B Nebgen, N Lubbers, O Isayev, AE Roitberg The Journal of Chemical Physics 148 (24), 241733, 2018 | 626 | 2018 |
| Approaching coupled cluster accuracy with a general-purpose neural network potential through transfer learning J S Smith, BT Nebgen, R Zubatyuk, N Lubbers, C Devereux, K Barros, ... Nature Communications 10 (2903), 2019 | 581 | 2019 |
| Hierarchical modeling of molecular energies using a deep neural network N Lubbers, JS Smith, K Barros The Journal of Chemical Physics 148 (24), 241715, 2018 | 302 | 2018 |
| ANI-1, A data set of 20 million calculated off-equilibrium conformations for organic molecules JS Smith, O Isayev, AE Roitberg Scientific Data 4, 170193, 2017 | 266 | 2017 |
| Extending the applicability of the ANI deep learning molecular potential to sulfur and halogens C Devereux, JS Smith, KK Huddleston, K Barros, R Zubatyuk, O Isayev, ... Journal of Chemical Theory and Computation 16 (7), 4192-4202, 2020 | 231 | 2020 |
| TorchANI: A Free and Open Source PyTorch-Based Deep Learning Implementation of the ANI Neural Network Potentials X Gao, F Ramezanghorbani, O Isayev, JS Smith, AE Roitberg Journal of chemical information and modeling 60 (7), 3408-3415, 2020 | 204 | 2020 |
| Accurate and transferable multitask prediction of chemical properties with an atoms-in-molecules neural network R Zubatyuk, JS Smith, J Leszczynski, O Isayev Science Advances 5 (8), eaav6490, 2019 | 192 | 2019 |
| The ANI-1ccx and ANI-1x data sets, coupled-cluster and density functional theory properties for molecules JS Smith, R Zubatyuk, B Nebgen, N Lubbers, K Barros, AE Roitberg, ... Scientific data 7 (1), 134, 2020 | 168 | 2020 |
| Discovering a transferable charge assignment model using machine learning AE Sifain, N Lubbers, BT Nebgen, JS Smith, AY Lokhov, O Isayev, ... The journal of physical chemistry letters 9 (16), 4495-4501, 2018 | 118 | 2018 |
| Transferable Dynamic Molecular Charge Assignment Using Deep Neural Networks B Nebgen, N Lubbers, JS Smith, AE Sifain, A Lokhov, O Isayev, ... Journal of chemical theory and computation, 2018 | 106 | 2018 |
| Transforming Computational Drug Discovery with Machine Learning and AI JS Smith, AE Roitberg, O Isayev ACS medicinal chemistry letters 9 (11), 1065-1069, 2018 | 97 | 2018 |
| Teaching a neural network to attach and detach electrons from molecules R Zubatyuk, JS Smith, BT Nebgen, S Tretiak, O Isayev Nature Communications 12 (1), 4870, 2021 | 73 | 2021 |
| Automated discovery of a robust interatomic potential for aluminum JS Smith, B Nebgen, N Mathew, J Chen, N Lubbers, L Burakovsky, ... Nature communications 12 (1), 1257, 2021 | 67 | 2021 |
| Extending machine learning beyond interatomic potentials for predicting molecular properties N Fedik, R Zubatyuk, M Kulichenko, N Lubbers, JS Smith, B Nebgen, ... Nature Reviews Chemistry 6 (9), 653-672, 2022 | 55 | 2022 |
| The Rise of Neural Networks for Materials and Chemical Dynamics M Kulichenko, JS Smith, B Nebgen, YW Li, N Fedik, AI Boldyrev, ... The Journal of Physical Chemistry Letters 12 (26), 6227-6243, 2021 | 51 | 2021 |
| Machine learned Hückel theory: Interfacing physics and deep neural networks T Zubatiuk, B Nebgen, N Lubbers, JS Smith, R Zubatyuk, G Zhou, C Koh, ... The Journal of Chemical Physics 154 (24), 2021 | 40 | 2021 |
| Modeling of Peptides with Classical and Novel Machine Learning Force Fields: A Comparison D Rosenberger, JS Smith, AE Garcia The Journal of Physical Chemistry B 125 (14), 3598-3612, 2021 | 34 | 2021 |
| Machine learning for molecular dynamics with strongly correlated electrons H Suwa, JS Smith, N Lubbers, CD Batista, GW Chern, K Barros Physical Review B 99 (16), 161107, 2019 | 33 | 2019 |
| Enantioselectivity in the Noyori–Ikariya Asymmetric Transfer Hydrogenation of Ketones PA Dub, NV Tkachenko, VK Vyas, M Wills, JS Smith, S Tretiak Organometallics 40 (9), 1402-1410, 2021 | 30 | 2021 |
Olexandr IsayevAssociate Professor, Carnegie Mellon UniversityVerified email at olexandrisayev.com
