activity
20232026
most citedForward and Inverse Simulation of Pseudo-Two-Dimensional Model of Lithium-Ion Batteries Using Neural Networks

11 citations · 19 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2026

Error as Signal: Stiffness-Aware Diffusion Sampling via Embedded Runge-Kutta Guidance

Inho Kong, Sojin Lee, Youngjoon Hong +1

Classifier-Free Guidance (CFG) has established the foundation for guidance mechanisms in diffusion models, showing that well-designed guidance proxies significantly improve conditi…

cs.LG2025

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…

physics.comp-ph2024★ 11 cited

Forward and Inverse Simulation of Pseudo-Two-Dimensional Model of Lithium-Ion Batteries Using Neural Networks

Myeong-Su Lee, Jaemin Oh, Dong-Chan Lee +3

In this work, we address the challenges posed by the high nonlinearity of the Butler-Volmer (BV) equation in forward and inverse simulations of the pseudo-two-dimensional (P2D) mod…

cs.LG2024

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…

cs.LG2024

Constant Acceleration Flow

Dogyun Park, Sojin Lee, Sihyeon Kim +3

Rectified flow and reflow procedures have significantly advanced fast generation by progressively straightening ordinary differential equation (ODE) flows. They operate under the a…

math.NA2024★ 8 cited

Separable Physics-informed Neural Networks for Solving the BGK Model of the Boltzmann Equation

Jaemin Oh, Seung Yeon Cho, Seok-Bae Yun +2

In this study, we introduce a method based on Separable Physics-Informed Neural Networks (SPINNs) for effectively solving the BGK model of the Boltzmann equation. While the mesh-fr…

cs.CV2023

Hydra: Multi-head Low-rank Adaptation for Parameter Efficient Fine-tuning

Sanghyeon Kim, Hyunmo Yang, Younghyun Kim +2

The recent surge in large-scale foundation models has spurred the development of efficient methods for adapting these models to various downstream tasks. Low-rank adaptation method…