7 papers
Diffusion-Based Refinement for Kilometer-Scale Probabilistic Precipitation Nowcasting
Dohyun Park, Changhoon Song, Tengyuan Chang +2
Localized extreme precipitation is a major trigger of urban flash floods and landslides, yet producing nowcasts that combine fine spatial detail with probabilistic uncertainty rema…
Semi-Supervised Neural Super-Resolution for Mesh-Based Simulations
Jiyeon Kim, Youngjoon Hong, Won-Yong Shin
Mesh-based simulations provide high-fidelity solutions to partial differential equations (PDEs), but achieving such accuracy typically requires fine meshes, leading to substantial…
Extreme Weather Nowcasting via Local Precipitation Pattern Prediction
Changhoon Song, Teng Yuan Chang, Youngjoon Hong
Accurate forecasting of extreme weather events such as heavy rainfall or storms is critical for risk management and disaster mitigation. Although high-resolution radar observations…
Singular layer PINN methods for Burgers' equation
Teng-Yuan Chang, Gung-Min Gie, Youngjoon Hong +1
In this article, we present a new learning method called sl-PINN to tackle the one-dimensional viscous Burgers problem at a small viscosity, which results in a singular interior la…
Semi-analytic PINN methods for boundary layer problems in a rectangular domain
Gung-Min Gie, Youngjoon Hong, Chang-Yeol Jung +1
Singularly perturbed boundary value problems pose a significant challenge for their numerical approximations because of the presence of sharp boundary layers. These sharp boundary…
Singular Layer Physics-Informed Neural Network Method for Convection-Dominated Boundary Layer Problems in Two Dimensions
Gung-Min Gie, Youngjoon Hong, Chang-Yeol Jung +1
This research explores neural network-based numerical approximation of two-dimensional convection-dominated singularly perturbed problems on square, circular, and elliptic domains.…
Singular layer Physics Informed Neural Network method for Plane Parallel Flows
Teng-Yuan Chang, Gung-Min Gie, Youngjoon Hong +1
We construct in this article the semi-analytic Physics Informed Neural Networks (PINNs), called {\em singular layer PINNs} (or {\em sl-PINNs}), that are suitable to predict the sti…