Pde-refiner: Achieving accurate long rollouts with neural pde solvers

P Lippe, B Veeling, P Perdikaris… - Advances in …, 2023 - proceedings.neurips.cc
Time-dependent partial differential equations (PDEs) are ubiquitous in science and
engineering. Recently, mostly due to the high computational cost of traditional solution …

Adversarial learning for neural pde solvers with sparse data

Y Gong, Y Hou, Z Wang, Z Lin, M Jiang - arXiv preprint arXiv:2409.02431, 2024 - arxiv.org
Neural network solvers for partial differential equations (PDEs) have made significant
progress, yet they continue to face challenges related to data scarcity and model robustness …