| Relational inductive biases, deep learning, and graph networks PW Battaglia, JB Hamrick, V Bapst, A Sanchez-Gonzalez, V Zambaldi, ... arXiv preprint arXiv:1806.01261, 2018 | 3604 | 2018 |
| Learning to simulate complex physics with graph networks A Sanchez-Gonzalez, J Godwin, T Pfaff, R Ying, J Leskovec, P Battaglia International conference on machine learning, 8459-8468, 2020 | 1027 | 2020 |
| Learning mesh-based simulation with graph networks T Pfaff, M Fortunato, A Sanchez-Gonzalez, PW Battaglia arXiv preprint arXiv:2010.03409, 2020 | 708 | 2020 |
| Graph networks as learnable physics engines for inference and control A Sanchez-Gonzalez, N Heess, JT Springenberg, J Merel, M Riedmiller, ... International conference on machine learning, 4470-4479, 2018 | 688 | 2018 |
| Discovering symbolic models from deep learning with inductive biases M Cranmer, A Sanchez Gonzalez, P Battaglia, R Xu, K Cranmer, ... Advances in neural information processing systems 33, 17429-17442, 2020 | 501 | 2020 |
| Learning skillful medium-range global weather forecasting R Lam, A Sanchez-Gonzalez, M Willson, P Wirnsberger, M Fortunato, ... Science 382 (6677), 1416-1421, 2023 | 370* | 2023 |
| Eta prediction with graph neural networks in google maps A Derrow-Pinion, J She, D Wong, O Lange, T Hester, L Perez, ... Proceedings of the 30th ACM International Conference on Information …, 2021 | 218 | 2021 |
| Hamiltonian graph networks with ode integrators A Sanchez-Gonzalez, V Bapst, K Cranmer, P Battaglia arXiv preprint arXiv:1909.12790, 2019 | 160 | 2019 |
| Compile: Compositional imitation learning and execution T Kipf, Y Li, H Dai, V Zambaldi, A Sanchez-Gonzalez, E Grefenstette, ... International Conference on Machine Learning, 3418-3428, 2019 | 138* | 2019 |
| Ultrafast isomerization initiated by X-ray core ionization CE Liekhus-Schmaltz, I Tenney, T Osipov, A Sanchez-Gonzalez, N Berrah, ... Nature communications 6 (1), 8199, 2015 | 122 | 2015 |
| Structured agents for physical construction V Bapst, A Sanchez-Gonzalez, C Doersch, K Stachenfeld, P Kohli, ... International conference on machine learning, 464-474, 2019 | 110 | 2019 |
| Simple gnn regularisation for 3d molecular property prediction & beyond J Godwin, M Schaarschmidt, A Gaunt, A Sanchez-Gonzalez, Y Rubanova, ... arXiv preprint arXiv:2106.07971, 2021 | 109 | 2021 |
| Learned coarse models for efficient turbulence simulation K Stachenfeld, DB Fielding, D Kochkov, M Cranmer, T Pfaff, J Godwin, ... arXiv preprint arXiv:2112.15275, 2021 | 89* | 2021 |
| Accurate prediction of X-ray pulse properties from a free-electron laser using machine learning A Sanchez-Gonzalez, P Micaelli, C Olivier, TR Barillot, M Ilchen, ... Nature communications 8 (1), 15461, 2017 | 88 | 2017 |
| Linac Coherent Light Source data analysis using psana D Damiani, M Dubrovin, I Gaponenko, W Kroeger, TJ Lane, A Mitra, ... Journal of Applied Crystallography 49 (2), 672-679, 2016 | 87 | 2016 |
| Pre-training via denoising for molecular property prediction S Zaidi, M Schaarschmidt, J Martens, H Kim, YW Teh, ... arXiv preprint arXiv:2206.00133, 2022 | 84 | 2022 |
| Combining q-learning and search with amortized value estimates JB Hamrick, V Bapst, A Sanchez-Gonzalez, T Pfaff, T Weber, L Buesing, ... arXiv preprint arXiv:1912.02807, 2019 | 56 | 2019 |
| Experimental simulation of simultaneous vision P de Gracia, C Dorronsoro, Á Sánchez-González, L Sawides, S Marcos Investigative ophthalmology & visual science 54 (1), 415-422, 2013 | 56 | 2013 |
| Correlation-driven transient hole dynamics resolved in space and time in the isopropanol molecule T Barillot, O Alexander, B Cooper, T Driver, D Garratt, S Li, A Al Haddad, ... Physical Review X 11 (3), 031048, 2021 | 41 | 2021 |
| Physical design using differentiable learned simulators KR Allen, T Lopez-Guevara, K Stachenfeld, A Sanchez-Gonzalez, ... arXiv preprint arXiv:2202.00728, 2022 | 37 | 2022 |
