Youngkyu Lee

According to our database, Youngkyu Lee authored at least 11 papers between 2022 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Balanced group convolution: an improved group convolution based on approximability estimates.

Youngkyu Lee, Jongho Park, Chang-Ock Lee

Pattern Anal. Appl., December, 2025

Residual-guided AI-CFD hybrid method enables stable and scalable simulations: from 2D benchmarks to 3D applications.

Shilaj Baral, Youngkyu Lee, Sangam Khanal, Joongoo Jeon

CoRR, October, 2025

Leveraging Operator Learning to Accelerate Convergence of the Preconditioned Conjugate Gradient Method.

Alena Kopanicáková, Youngkyu Lee, George Em Karniadakis

CoRR, August, 2025

Automatic discovery of optimal meta-solvers for time-dependent nonlinear PDEs.

Youngkyu Lee, Shanqing Liu, Jérôme Darbon, George Em Karniadakis

CoRR, July, 2025

Physics-Guided Multi-Fidelity DeepONet for Data-Efficient Flow Field Prediction.

Sunwoong Yang, Youngkyu Lee, Namwoo Kang

CoRR, March, 2025

A nonoverlapping domain decomposition method for extreme learning machines: Elliptic problems.

Chang-Ock Lee, Youngkyu Lee, Byungeun Ryoo

Comput. Math. Appl., 2025

2024

Parareal Neural Networks Emulating a Parallel-in-Time Algorithm.

Youngkyu Lee, Jongho Park, Chang-Ock Lee

IEEE Trans. Neural Networks Learn. Syst., May, 2024

Automatic discovery of optimal meta-solvers via multi-objective optimization.

Youngkyu Lee, Shanqing Liu, Jérôme Darbon, George Em Karniadakis

CoRR, 2024

Two-level overlapping additive Schwarz preconditioner for training scientific machine learning applications.

Youngkyu Lee, Alena Kopanicáková, George Em Karniadakis

CoRR, 2024

2023

Balanced Group Convolution: An Improved Group Convolution Based on Approximability Estimates.

Youngkyu Lee, Jongho Park, Chang-Ock Lee

CoRR, 2023

2022

Two-level group convolution.

Youngkyu Lee, Jongho Park, Chang-Ock Lee

Neural Networks, 2022