| Grandmaster level in StarCraft II using multi-agent reinforcement learning O Vinyals, I Babuschkin, WM Czarnecki, M Mathieu, A Dudzik, J Chung, ... Nature 575 (7782), 350-354, 2019 | 4109 | 2019 |
| 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 (ICML 2020), 8459-8468, 2020 | 969 | 2020 |
| Learning mesh-based simulation with graph networks T Pfaff, M Fortunato, A Sanchez-Gonzalez, PW Battaglia International Conference on Learning Representations (ICLR 2021), 2021 | 650 | 2021 |
| Alphastar: Mastering the real-time strategy game starcraft ii O Vinyals, I Babuschkin, J Chung, M Mathieu, M Jaderberg, ... DeepMind blog 2, 20, 2019 | 540 | 2019 |
| Playing hard exploration games by watching youtube Y Aytar, T Pfaff, D Budden, TL Paine, Z Wang, N de Freitas Neural Information Processing Systems (NeurIPS 2018), 2018 | 295 | 2018 |
| Folding and crumpling adaptive sheets R Narain, T Pfaff, JF O'Brien ACM Transactions on Graphics (TOG) 32 (4), 1-8, 2013 | 173 | 2013 |
| Adaptive tearing and cracking of thin sheets T Pfaff, R Narain, JM De Joya, JF O'Brien ACM Transactions on Graphics (TOG) 33 (4), 1-9, 2014 | 117 | 2014 |
| Scalable fluid simulation using anisotropic turbulence particles T Pfaff, N Thuerey, J Cohen, S Tariq, M Gross ACM SIGGRAPH Asia 2010 papers, 1-8, 2010 | 116 | 2010 |
| Lagrangian vortex sheets for animating fluids T Pfaff, N Thuerey, M Gross ACM Transactions on Graphics (TOG) 31 (4), 1-8, 2012 | 104 | 2012 |
| Synthetic turbulence using artificial boundary layers T Pfaff, N Thuerey, A Selle, M Gross ACM SIGGRAPH Asia 2009 papers, 1-10, 2009 | 104 | 2009 |
| Learned Coarse Models for Efficient Turbulence Simulation K Stachenfeld, DB Fielding, D Kochkov, M Cranmer, T Pfaff, J Godwin, ... International Conference on Learning Representations (ICLR 2021), 2021 | 87* | 2021 |
| Predicting Physics in Mesh-reduced Space with Temporal Attention X Han, H Gao, T Pfaff, JX Wang, LP Liu International Conference on Machine Learning Representations (ICLR 2022), 2022 | 69 | 2022 |
| MantaFlow N Thuerey, T Pfaff URL: http://mantaflow. com, 2018 | 64* | 2018 |
| Field-scale apparent hydraulic parameterisation obtained from TDR time series and inverse modelling U Wollschläger, T Pfaff, K Roth Hydrology and Earth System Sciences 13 (10), 1953-1966, 2009 | 57* | 2009 |
| Combining q-learning and search with amortized value estimates JB Hamrick, V Bapst, A Sanchez-Gonzalez, T Pfaff, T Weber, L Buesing, ... International Conference on Learning Representations (ICLR 2020), 2020 | 56 | 2020 |
| Multiscale meshgraphnets M Fortunato, T Pfaff, P Wirnsberger, A Pritzel, P Battaglia arXiv preprint arXiv:2210.00612, 2022 | 48 | 2022 |
| Physical Design using Differentiable Learned Simulators KR Allen, T Lopez-Guevara, K Stachenfeld, A Sanchez-Gonzalez, ... Neural Information Processing Systems (NeurIPS 2022), 2022 | 42* | 2022 |
| One-shot high-fidelity imitation: Training large-scale deep nets with rl TL Paine, SG Colmenarejo, Z Wang, S Reed, Y Aytar, T Pfaff, ... arXiv preprint arXiv:1810.05017, 2018 | 25 | 2018 |
| Clothing model generation and display system JF O'brien, DT Jackson, C Camporesi, D Ram, D Macy, E de Aguiar, ... US Patent 11,164,381, 2021 | 24 | 2021 |
| Graph network simulators can learn discontinuous, rigid contact dynamics KR Allen, TL Guevara, Y Rubanova, K Stachenfeld, A Sanchez-Gonzalez, ... Conference on Robot Learning, 1157-1167, 2023 | 23 | 2023 |
