16 citations · 20 across the 2 of their papers we have counts for
2 papers
cs.LG2023★ 4 cited
Learning Controllable Adaptive Simulation for Multi-resolution Physics
Tailin Wu, Takashi Maruyama, Qingqing Zhao +2
Simulating the time evolution of physical systems is pivotal in many scientific and engineering problems. An open challenge in simulating such systems is their multi-resolution dyn…
cs.LG2022★ 16 cited
Learning to Solve PDE-constrained Inverse Problems with Graph Networks
Qingqing Zhao, David B. Lindell, Gordon Wetzstein
Learned graph neural networks (GNNs) have recently been established as fast and accurate alternatives for principled solvers in simulating the dynamics of physical systems. In many…