6 citations · 9 across the 2 of their papers we have counts for
2 papers
cs.LG2024★ 6 cited
Parameterized Physics-informed Neural Networks for Parameterized PDEs
Woojin Cho, Minju Jo, Haksoo Lim +4
Complex physical systems are often described by partial differential equations (PDEs) that depend on parameters such as the Reynolds number in fluid mechanics. In applications such…
cs.LG2023★ 3 cited
Hypernetwork-based Meta-Learning for Low-Rank Physics-Informed Neural Networks
Woojin Cho, Kookjin Lee, Donsub Rim +1
In various engineering and applied science applications, repetitive numerical simulations of partial differential equations (PDEs) for varying input parameters are often required (…