| Understanding the diversity of the metal-organic framework ecosystem SM Moosavi, A Nandy, KM Jablonka, D Ongari, JP Janet, PG Boyd, Y Lee, ... Nature communications 11 (1), 1-10, 2020 | 455 | 2020 |
| Resolving transition metal chemical space: Feature selection for machine learning and structure–property relationships JP Janet, HJ Kulik The Journal of Physical Chemistry A 121 (46), 8939-8954, 2017 | 273 | 2017 |
| Accelerating chemical discovery with machine learning: simulated evolution of spin crossover complexes with an artificial neural network JP Janet, L Chan, HJ Kulik The journal of physical chemistry letters 9 (5), 1064-1071, 2018 | 215 | 2018 |
| Predicting electronic structure properties of transition metal complexes with neural networks JP Janet, HJ Kulik Chemical science 8 (7), 5137-5152, 2017 | 214 | 2017 |
| A quantitative uncertainty metric controls error in neural network-driven chemical discovery JP Janet, C Duan, T Yang, A Nandy, HJ Kulik Chemical science 10 (34), 7913-7922, 2019 | 206 | 2019 |
| Accurate multiobjective design in a space of millions of transition metal complexes with neural-network-driven efficient global optimization JP Janet, S Ramesh, C Duan, HJ Kulik ACS central science 6 (4), 513-524, 2020 | 162 | 2020 |
| Strategies and software for machine learning accelerated discovery in transition metal chemistry A Nandy, C Duan, JP Janet, S Gugler, HJ Kulik Industrial & Engineering Chemistry Research 57 (42), 13973-13986, 2018 | 160 | 2018 |
| Designing in the face of uncertainty: exploiting electronic structure and machine learning models for discovery in inorganic chemistry JP Janet, F Liu, A Nandy, C Duan, T Yang, S Lin, HJ Kulik Inorganic chemistry 58 (16), 10592-10606, 2019 | 102 | 2019 |
| Machine learning accelerates the discovery of design rules and exceptions in stable metal–oxo intermediate formation A Nandy, J Zhu, JP Janet, C Duan, RB Getman, HJ Kulik Acs Catalysis 9 (9), 8243-8255, 2019 | 92 | 2019 |
| Learning from failure: predicting electronic structure calculation outcomes with machine learning models C Duan, JP Janet, F Liu, A Nandy, HJ Kulik Journal of Chemical Theory and Computation 15 (4), 2331-2345, 2019 | 87 | 2019 |
| Heterogeneous nucleation in CFD simulation of flashing flows in converging–diverging nozzles JP Janet, Y Liao, D Lucas International Journal of Multiphase Flow 74, 106-117, 2015 | 83 | 2015 |
| Seeing is believing: Experimental spin states from machine learning model structure predictions MG Taylor, T Yang, S Lin, A Nandy, JP Janet, C Duan, HJ Kulik The Journal of Physical Chemistry A 124 (16), 3286-3299, 2020 | 68 | 2020 |
| Machine Learning in Chemistry JP Janet, HJ Kulik American Chemical Society, 2020 | 64 | 2020 |
| Leveraging cheminformatics strategies for inorganic discovery: application to redox potential design JP Janet, TZH Gani, AH Steeves, EI Ioannidis, HJ Kulik Industrial & Engineering Chemistry Research 56 (17), 4898-4910, 2017 | 60 | 2017 |
| Graph neural networks with adaptive readouts D Buterez, JP Janet, SJ Kiddle, D Oglic, P Liò Advances in Neural Information Processing Systems 35, 19746-19758, 2022 | 57 | 2022 |
| DockStream: a docking wrapper to enhance de novo molecular design J Guo, JP Janet, MR Bauer, E Nittinger, KA Giblin, K Papadopoulos, ... Journal of cheminformatics 13, 1-21, 2021 | 57 | 2021 |
| Navigating transition-metal chemical space: artificial intelligence for first-principles design JP Janet, C Duan, A Nandy, F Liu, HJ Kulik Accounts of Chemical Research 54 (3), 532-545, 2021 | 52 | 2021 |
| Communication: Recovering the flat-plane condition in electronic structure theory at semi-local DFT cost A Bajaj, JP Janet, HJ Kulik The Journal of Chemical Physics 147 (19), 2017 | 51 | 2017 |
| Reinvent 4: Modern AI–driven generative molecule design HH Loeffler, J He, A Tibo, JP Janet, A Voronov, LH Mervin, O Engkvist Journal of Cheminformatics 16 (1), 20, 2024 | 50 | 2024 |
| Density functional theory for modelling large molecular adsorbate–surface interactions: a mini-review and worked example JP Janet, Q Zhao, EI Ioannidis, HJ Kulik Molecular Simulation 43 (5-6), 327-345, 2017 | 45 | 2017 |