| Neural message passing for quantum chemistry J Gilmer, SS Schoenholz, PF Riley, O Vinyals, GE Dahl International conference on machine learning, 1263-1272, 2017 | 3772 | 2017 |
| Molecular graph convolutions: moving beyond fingerprints S Kearnes, K McCloskey, M Berndl, V Pande, P Riley Journal of computer-aided molecular design 30 (8), 595-608, 2016 | 1111 | 2016 |
| Prediction errors of molecular machine learning models lower than hybrid DFT error FA Faber, L Hutchison, B Huang, J Gilmer, SS Schoenholz, GE Dahl, ... Journal of chemical theory and computation 13 (11), 5255-5264, 2017 | 471 | 2017 |
| Massively multitask networks for drug discovery B Ramsundar, S Kearnes, P Riley, D Webster, D Konerding, V Pande arXiv preprint arXiv:1502.02072, 2015 | 470 | 2015 |
| Tensor field networks: Rotation-and translation-equivariant neural networks for 3d point clouds N Thomas, T Smidt, S Kearnes, L Yang, L Li, K Kohlhoff, P Riley arXiv preprint arXiv:1802.08219, 2018 | 340 | 2018 |
| Optimization of molecules via deep reinforcement learning Z Zhou, S Kearnes, L Li, RN Zare, P Riley Scientific reports 9 (1), 1-10, 2019 | 298 | 2019 |
| Proceedings of the 34th International Conference on Machine Learning J Gilmer, SS Schoenholz, PF Riley, O Vinyals, GE Dahl PMLR 70, 1263-1272, 2017 | 131 | 2017 |
| Spades-a distributed agent simulation environment with software-in-the-loop execution PF Riley, GF Riley Georgia Institute of Technology, 2003 | 128 | 2003 |
| The CMUnited-99 champion simulator team P Stone, P Riley, M Veloso Robot Soccer World Cup, 35-48, 1999 | 126 | 1999 |
| The CMUnited-98 champion simulator team P Stone, M Veloso, P Riley Robot Soccer World Cup, 61-76, 1998 | 113 | 1998 |
| On behavior classification in adversarial environments P Riley, M Veloso Distributed autonomous robotic systems 4, 371-380, 2000 | 111 | 2000 |
| Three pitfalls to avoid in machine learning P Riley Nature 572 (7767), 27-29, 2019 | 96 | 2019 |
| Defining and using ideal teammate and opponent agent models P Stone, P Riley, M Veloso AAAI/IAAI, 1040-1045, 2000 | 87 | 2000 |
| Planning for Distributed Execution through Use of Probabilistic Opponent Models. P Riley, MM Veloso AIPS, 72-82, 2002 | 82 | 2002 |
| Recognizing probabilistic opponent movement models P Riley, M Veloso Robot Soccer World Cup, 453-458, 2001 | 79 | 2001 |
| A Bayesian experimental autonomous researcher for mechanical design AE Gongora, B Xu, W Perry, C Okoye, P Riley, KG Reyes, EF Morgan, ... Science advances 6 (15), eaaz1708, 2020 | 69 | 2020 |
| Kohn-Sham equations as regularizer: Building prior knowledge into machine-learned physics L Li, S Hoyer, R Pederson, R Sun, ED Cubuk, P Riley, K Burke Physical review letters 126 (3), 036401, 2021 | 65 | 2021 |
| An empirical study of coaching P Riley, M Veloso, G Kaminka Distributed Autonomous Robotic Systems 5, 215-224, 2002 | 65 | 2002 |
| Deep diversification of an AAV capsid protein by machine learning DH Bryant, A Bashir, S Sinai, NK Jain, PJ Ogden, PF Riley, GM Church, ... Nature Biotechnology 39 (6), 691-696, 2021 | 61 | 2021 |
| Quantum optimization with a novel gibbs objective function and ansatz architecture search L Li, M Fan, M Coram, P Riley, S Leichenauer Physical Review Research 2 (2), 023074, 2020 | 53 | 2020 |
