| Automatic chemical design using a data-driven continuous representation of molecules R Gómez-Bombarelli, JN Wei, D Duvenaud, JM Hernández-Lobato, ... ACS central science 4 (2), 268-276, 2018 | 1815 | 2018 |
| Inverse molecular design using machine learning: Generative models for matter engineering B Sanchez-Lengeling, A Aspuru-Guzik Science 361 (6400), 360-365, 2018 | 870 | 2018 |
| Objective-reinforced generative adversarial networks (ORGAN) for sequence generation models GL Guimaraes, B Sanchez-Lengeling, C Outeiral, PLC Farias, ... arXiv preprint arXiv:1705.10843, 2017 | 364 | 2017 |
| Reinforced Adversarial Neural Computer for de Novo Molecular Design E Putin, A Asadulaev, Y Ivanenkov, V Aladinskiy, B Sanchez-Lengeling, ... Journal of chemical information and modeling 58 (6), 1194-1204, 2018 | 220 | 2018 |
| Molecular sets (MOSES): a benchmarking platform for molecular generation models D Polykovskiy, A Zhebrak, B Sanchez-Lengeling, S Golovanov, O Tatanov, ... Frontiers in pharmacology 11, 1931, 2020 | 218* | 2020 |
| Rational design of layered oxide materials for sodium-ion batteries C Zhao, Q Wang, Z Yao, J Wang, B Sánchez-Lengeling, F Ding, X Qi, ... Science 370 (6517), 708-711, 2020 | 213 | 2020 |
| Optimizing distributions over molecular space. An objective-reinforced generative adversarial network for inverse-design chemistry (ORGANIC) B Sanchez-Lengeling, C Outeiral, GL Guimaraes, A Aspuru-Guzik | 204 | 2017 |
| Design principles and top non-fullerene acceptor candidates for organic photovoltaics SA Lopez, B Sanchez-Lengeling, J de Goes Soares, A Aspuru-Guzik Joule 1 (4), 857-870, 2017 | 137 | 2017 |
| Inverse design of solid-state materials via a continuous representation J Noh, J Kim, HS Stein, B Sanchez-Lengeling, JM Gregoire, ... Matter 1 (5), 1370-1384, 2019 | 134 | 2019 |
| Inverse design of nanoporous crystalline reticular materials with deep generative models Z Yao, B Sánchez-Lengeling, NS Bobbitt, BJ Bucior, SGH Kumar, ... Nature Machine Intelligence 3 (1), 76-86, 2021 | 86 | 2021 |
| A Mixed quantum chemistry/machine learning approach for the fast and accurate prediction of biochemical redox potentials and its large-scale application to 315 000 redox reactions A Jinich, B Sanchez-Lengeling, H Ren, R Harman, A Aspuru-Guzik ACS central science 5 (7), 1199-1210, 2019 | 49 | 2019 |
| Quantum chemical approach to estimating the thermodynamics of metabolic reactions A Jinich, D Rappoport, I Dunn, B Sanchez-Lengeling, R Olivares-Amaya, ... Scientific reports 4 (1), 1-6, 2014 | 49 | 2014 |
| Machine learning for scent: Learning generalizable perceptual representations of small molecules B Sanchez-Lengeling, JN Wei, BK Lee, RC Gerkin, A Aspuru-Guzik, ... arXiv preprint arXiv:1910.10685, 2019 | 47 | 2019 |
| A Bayesian approach to predict solubility parameters B Sanchez‐Lengeling, LM Roch, JD Perea, S Langner, CJ Brabec, ... Advanced Theory and Simulations 2 (1), 1800069, 2019 | 46 | 2019 |
| Introducing a new potential figure of merit for evaluating microstructure stability in photovoltaic polymer-fullerene blends JD Perea, S Langner, M Salvador, B Sanchez-Lengeling, N Li, C Zhang, ... The Journal of Physical Chemistry C 121 (33), 18153-18161, 2017 | 46 | 2017 |
| Materials acceleration platforms: On the way to autonomous experimentation MM Flores-Leonar, LM Mejía-Mendoza, A Aguilar-Granda, ... Current Opinion in Green and Sustainable Chemistry 25, 100370, 2020 | 40 | 2020 |
| Evaluating attribution for graph neural networks B Sanchez-Lengeling, J Wei, B Lee, E Reif, P Wang, W Qian, ... Advances in neural information processing systems 33, 5898-5910, 2020 | 38* | 2020 |
| Quantum chemistry reveals thermodynamic principles of redox biochemistry A Jinich, A Flamholz, H Ren, SJ Kim, B Sanchez-Lengeling, CAR Cotton, ... PLoS computational biology 14 (10), e1006471, 2018 | 26 | 2018 |
| A Quantum Monte Carlo Study of the Reactions of CH with Acrolein S Pakhira, B Sanchez-Lengeling, O Olatunji-Ojo, M Caffarel, M Frenklach, ... The Journal of Physical Chemistry A 119 (18), 4214-4223, 2015 | 25 | 2015 |
| A machine learning workflow for molecular analysis: application to melting points G Sivaraman, NE Jackson, B Sanchez-Lengeling, Á Vázquez-Mayagoitia, ... Machine Learning: Science and Technology 1 (2), 025015, 2020 | 16 | 2020 |
Alan Aspuru-GuzikProfessor of Chemistry and Computer Science, University of Toronto (starting July 1, 2018)Verified email at utoronto.ca
