| 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 | 3933 | 2018 |
| A simple neural network module for relational reasoning A Santoro, D Raposo, DG Barrett, M Malinowski, R Pascanu, P Battaglia, ... Advances in neural information processing systems 30, 2017 | 1937 | 2017 |
| Interaction networks for learning about objects, relations and physics P Battaglia, R Pascanu, M Lai, DJ Rezende, K Kavukcuoglu Advances in Neural Information Processing Systems 2016, 4502-4510, 2016 | 1732 | 2016 |
| 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 | 1249 | 2020 |
| Simulation as an engine of physical scene understanding PW Battaglia, JB Hamrick, JB Tenenbaum Proceedings of the National Academy of Sciences 110 (45), 18327-18332, 2013 | 990 | 2013 |
| Learning mesh-based simulation with graph networks T Pfaff, M Fortunato, A Sanchez-Gonzalez, PW Battaglia arXiv preprint arXiv:2010.03409, 2020 | 908 | 2020 |
| Learning deep generative models of graphs Y Li, O Vinyals, C Dyer, R Pascanu, P Battaglia arXiv preprint arXiv:1803.03324, 2018 | 755 | 2018 |
| 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 | 741 | 2018 |
| Bayesian integration of visual and auditory signals for spatial localization PW Battaglia, RA Jacobs, RN Aslin Josa a 20 (7), 1391-1397, 2003 | 615 | 2003 |
| 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 | 581 | 2020 |
| Lagrangian neural networks M Cranmer, S Greydanus, S Hoyer, P Battaglia, D Spergel, S Ho arXiv preprint arXiv:2003.04630, 2020 | 539 | 2020 |
| Deep reinforcement learning with relational inductive biases V Zambaldi, D Raposo, A Santoro, V Bapst, Y Li, I Babuschkin, K Tuyls, ... International conference on learning representations, 2019 | 528* | 2019 |
| Advancing mathematics by guiding human intuition with AI A Davies, P Veličković, L Buesing, S Blackwell, D Zheng, N Tomašev, ... Nature 600 (7887), 70-74, 2021 | 510 | 2021 |
| Learning skillful medium-range global weather forecasting R Lam, A Sanchez-Gonzalez, M Willson, P Wirnsberger, M Fortunato, ... Science 382 (6677), 1416-1421, 2023 | 488 | 2023 |
| Imagination-augmented agents for deep reinforcement learning S Racanière, T Weber, D Reichert, L Buesing, A Guez, ... Advances in neural information processing systems 30, 2017 | 483 | 2017 |
| Unsupervised learning of 3d structure from images D Jimenez Rezende, SM Eslami, S Mohamed, P Battaglia, M Jaderberg, ... Advances in neural information processing systems 29, 2016 | 460 | 2016 |
| Visual interaction networks: Learning a physics simulator from video N Watters, D Zoran, T Weber, P Battaglia, R Pascanu, A Tacchetti Advances in neural information processing systems 30, 2017 | 422 | 2017 |
| Graph neural networks in particle physics J Shlomi, P Battaglia, JR Vlimant Machine Learning: Science and Technology 2 (2), 021001, 2020 | 357 | 2020 |
| 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 | 285 | 2021 |
| Hyperbolic attention networks C Gulcehre, M Denil, M Malinowski, A Razavi, R Pascanu, KM Hermann, ... arXiv preprint arXiv:1805.09786, 2018 | 285 | 2018 |
Jessica B. HamrickResearch Scientist at DeepMind在 google.com 的电子邮件经过验证
