Fangxin Fang
Statistical and Nonlinear Physics · 2009–2017
A researcher in the Science corpus: 5 papers; trusts 13 researchers and is trusted by 2 researchers here, as inferred from the citation graph.
Subfields
- Statistical and Nonlinear Physics — 33 citations into it; #8,557 of 10,127 by trust here, #4,820 by citations
- Computational Mechanics — 32 citations into it; #8,721 of 10,001 by trust here, #6,041 by citations
- Statistics and Probability — 16 citations into it
- Numerical Analysis — 15 citations into it; #3,166 of 3,586 by trust here, #3,457 by citations
- Atmospheric Science — 10 citations into it
- Global and Planetary Change — 9 citations into it
- Computational Theory and Mathematics — 5 citations into it
Whom Fangxin Fang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Saifon Chaturantabut
- Ngoc Cuong Nguyen
- Christophe Audouze
- Christopher C. Pain
- Danny C. Sorensen
- Jaime Peraire
- Dacian N. Daescu
- Dunhui Xiao
- M. Couplet
- Thomas Gerstner
Who trusts Fangxin Fang overall
Papers from Fangxin Fang's perspective
Ordered by how strongly the researchers Fangxin Fang trusts endorse each paper. Same corpus, a different order for every researcher.
- EFFICIENT REDUCED-BASIS TREATMENT OF NONAFFINE AND NONLINEAR PARTIAL DIFFERENTIAL EQUATIONS
- A ‘best points’ interpolation method for efficient approximation of parametrized functions
- Galerkin Proper Orthogonal Decomposition Methods for a General Equation in Fluid Dynamics (SIAM Journal on Numerical Analysis)
- An efficient reduced‐order modeling approach for non‐linear parametrized partial differential equations
- Application of POD and DEIM on dimension reduction of non-linear miscible viscous fingering in porous media
- Nonlinear Model Reduction via Discrete Empirical Interpolation (SIAM Journal on Scientific Computing)
- LIII. On lines and planes of closest fit to systems of points in space
- Numerical integration using sparse grids (Numerical Algorithms)
- High dimensional polynomial interpolation on sparse grids (Advances in Computational Mathematics)
- Reduced Basis Methods for Partial Differential Equations: An Introduction
Their papers
- Non-linear Petrov-Galerkin methods for reduced order modelling of the Navier-Stokes equations using a mixed finite element pair (2013) — 92 citations
- A parameterized non-intrusive reduced order model and error analysis for general time-dependent nonlinear partial differential equations and its applications (2017) — 126 citations
- Non-intrusive reduced order modelling of the Navier-Stokes equations (2015) — 157 citations
- Non‐intrusive reduced‐order modelling of the Navier–Stokes equations based on RBF interpolation (2015) — 184 citations
- A POD reduced order unstructured mesh ocean modelling method for moderate Reynolds number flows (2009) — 86 citations