most citedAI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble

1 citations · 1 across the 4 of their papers we have counts for

collaborators

7 papers

physics.comp-ph2025

Point-wise Diffusion Models for Physical Systems with Shape Variations: Application to Spatio-temporal and Large-scale system

Jiyong Kim, Sunwoong Yang, Namwoo Kang

This study introduces a novel point-wise diffusion model that processes spatio-temporal points independently to efficiently predict complex physical systems with shape variations.…

cs.LG2025

Node Assigned physics-informed neural networks for thermal-hydraulic system simulation: CVH/FL module

Jeesuk Shin, Cheolwoong Kim, Sunwoong Yang +3

Severe accidents (SAs) in nuclear power plants have been analyzed using thermal-hydraulic (TH) system codes such as MELCOR and MAAP. These codes efficiently simulate the progressio…

cs.CE2025

Rigid-Deformation Decomposition AI Framework for 3D Spatio-Temporal Prediction of Vehicle Collision Dynamics

Sanghyuk Kim, Minsik Seo, Sunwoong Yang +1

This study presents a rigid-deformation decomposition framework for vehicle collision dynamics that mitigates the spectral bias of implicit neural representations, that is, coordin…

physics.flu-dyn2025

Data-Efficient Deep Operator Network for Unsteady Flow: A Multi-Fidelity Approach with Physics-Guided Subsampling

Sunwoong Yang, Youngkyu Lee, Namwoo Kang

This study presents an enhanced multi-fidelity Deep Operator Network (DeepONet) framework for efficient spatio-temporal flow field prediction when high-fidelity data is scarce. Key…

cs.LG20251 cited

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…

cs.LG2024

Model-Agnostic AI Framework with Explicit Time Integration for Long-Term Fluid Dynamics Prediction

Sunwoong Yang, Ricardo Vinuesa, Namwoo Kang

This study addresses the critical challenge of error accumulation in spatio-temporal auto-regressive (AR) predictions within scientific machine learning models by exploring tempora…