1 code implementation • 1 Apr 2024 • Jungeun Kim, Hangyul Yoon, Geondo Park, KyungSu Kim, Eunho Yang
4D medical images, which represent 3D images with temporal information, are crucial in clinical practice for capturing dynamic changes and monitoring long-term disease progression.
no code implementations • 29 Sep 2021 • Jungeun Kim, Seunghyun Hwang, Jeehyun Hwang, Kookjin Lee, Dongeun Lee, Noseong Park
In other words, the knowledge contained by the learned governing equation can be injected into the neural network which approximates the PDE solution function.
no code implementations • 1 Jan 2021 • Jungeun Kim, Seunghyun Hwang, Jihyun Hwang, Kookjin Lee, Dongeun Lee, Noseong Park
Neural ordinary differential equations (neural ODEs) introduced an approach to approximate a neural network as a system of ODEs after considering its layer as a continuous variable and discretizing its hidden dimension.
1 code implementation • 4 Dec 2020 • Jungeun Kim, Kookjin Lee, Dongeun Lee, Sheo Yon Jin, Noseong Park
We present a method for learning dynamics of complex physical processes described by time-dependent nonlinear partial differential equations (PDEs).