11 citations · 20 across the 9 of their papers we have counts for
5 papers · 1 filter
Perron--Frobenius Operator Matching for Generative Modeling
Shiqi Zhang, Wuwei Wu, Jaemin Oh +2
We introduce Perron--Frobenius Operator Matching (PFOM), a generative framework that matches density evolution via the integral PF operator, subsuming flow, diffusion, and jump mod…
On the Effect of Neural Field Reparameterization for 4DVAR
Jaemin Oh
Four-dimensional variational data assimilation (4DVAR) is a cornerstone of numerical weather prediction, yet it remains computationally intensive and sensitive to initialization du…
Neural Operator-Based Nonlinear Nudging for Chaotic Dynamical Systems
Jaemin Oh, Jinsil Lee, Youngjoon Hong
Nudging is an empirical data assimilation technique that incorporates an observation-driven control term into the model dynamics. The trajectory of the nudged system approaches the…
AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble
Dongeon Lee, Sunwoong Yang, Jae-Won Oh +3
Environmental pollution and fossil fuel depletion have prompted the need for renewable energy-based power generation. However, its stability is often challenged by low energy densi…
PIG: Physics-Informed Gaussians as Adaptive Parametric Mesh Representations
Namgyu Kang, Jaemin Oh, Youngjoon Hong +1
The numerical approximation of partial differential equations (PDEs) using neural networks has seen significant advancements through Physics-Informed Neural Networks (PINNs). Despi…