Haksoo Lim — accepted AI-conference papers

2025

Efficiently Parameterized Neural Metriplectic Systems

Anthony Gruber, Kookjin Lee, Haksoo Lim, Noseong Park, Nathaniel Trask

ICLR 2025poster

Metriplectic systems are learned from data in a way that scales quadratically in both the size of the state and the rank of the metriplectic operators. In addition to being provably energy-conserving and entropy-stable, the proposed neural metriplectic systems (NMS) approach includes approximation…

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2024

Parameterized Physics-informed Neural Networks for Parameterized PDEs

Woojin Cho, Minju Jo, Haksoo Lim, Kookjin Lee, Dongeun Lee, Sanghyun Hong +1

ICML 2024oral

Complex physical systems are often described by partial differential equations (PDEs) that depend on parameters such as the Raynolds number in fluid mechanics. In applications such as design optimization or uncertainty quantification, solutions of those PDEs need to be evaluated at numerous points i…

Cited by 23 Source ↗PDF ↗Scholar ↗