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researcher

S. Kim

2 papers hereh-index 211.8k citations119 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • last author2

Across the 2 of 2 papers where every author was matched, so the position is known.

fields
  • cs.LG1
  • physics.flu-dyn1
same name
  • S. Kim — 239 papers
  • S. Kim — 103 papers, h 66
  • S. Kim — 82 papers
  • S. Kim — 66 papers, h 18
  • S. Kim — 43 papers, h 51
  • S. Kim — 43 papers, h 21

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedResidual-based physics-informed transfer learning: A hybrid method for accelerating long-term CFD simulations via deep learning

62 citations · 62 across the 1 of their papers we have counts for

collaborators

2 papers

physics.flu-dyn2022★ 62 cited

Residual-based physics-informed transfer learning: A hybrid method for accelerating long-term CFD simulations via deep learning

Joongoo Jeon, Juhyeong Lee, Ricardo Vinuesa +1

While a big wave of artificial intelligence (AI) has propagated to the field of computational fluid dynamics (CFD) acceleration studies, recent research has highlighted that the de…

cs.LG2021

Finite volume method network for acceleration of unsteady computational fluid dynamics: non-reacting and reacting flows

Joongoo Jeon, Juhyeong Lee, Sung Joong Kim

Despite rapid improvements in the performance of central processing unit (CPU), the calculation cost of simulating chemically reacting flow using CFD remains infeasible in many cas…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.