850 citations · 2.5k across the 63 of their papers we have counts for
3 papers · 1 filter
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…
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…
Deep SPR: Simultaneous Source Separation and Phase Retrieval Using Deep Generative Models
Christopher A. Metzler, Gordon Wetzstein
This paper introduces and solves the simultaneous source separation and phase retrieval (SPR) problem. SPR is an important but largely unsolved problem in a number applicat…