Jiaqing Kou

Computational Mechanics · 2016–2018

A researcher in the Science corpus: 3 papers; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Jiaqing Kou trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Clarence W. Rowley
  2. Peter J. Schmid
  3. Karthik Duraisamy
  4. J. Nathan Kutz
  5. Anand Pratap Singh
  6. Shervin Bagheri
  7. Steven L. Brunton
  8. K. A. Abdul Nazeer

Papers from Jiaqing Kou's perspective

Ordered by how strongly the researchers Jiaqing Kou trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Machine learning strategies for systems with invariance properties (Journal of Computational Physics)
  2. New Approaches in Turbulence and Transition Modeling Using Data-driven Techniques
  3. Neural network modeling for near wall turbulent flow
  4. Turbulence Modeling in the Age of Data (Annual Review of Fluid Mechanics)
  5. Evaluation of machine learning algorithms for prediction of regions of high Reynolds averaged Navier Stokes uncertainty
  6. Deep learning in fluid dynamics (Journal of Fluid Mechanics)
  7. CFD Vision 2030 Study: A Path to Revolutionary Computational Aerosciences
  8. Three learning phases for radial-basis-function networks
  9. Local radial basis function-based differential quadrature method and its application to solve two-dimensional incompressible Navier–Stokes equations
  10. Machine Learning-augmented Predictive Modeling of Turbulent Separated Flows over Airfoils

Their papers