What is she best known for?
The fields of study she is best known for:
- Mathematical analysis
- Statistics
- Algebra
Her main research concerns Discrete mathematics, Quasi-Monte Carlo method, Mathematical analysis, Sobolev space and Lattice.
Frances Y. Kuo interconnects Euclidean space, Sobol sequence, Numerical integration, Algorithm and Numerical analysis in the investigation of issues within Discrete mathematics.
Her research in Quasi-Monte Carlo method intersects with topics in Elliptic partial differential equation, Class, Finite element method and Applied mathematics.
Her Applied mathematics research is multidisciplinary, relying on both Unit cube and Bounded function.
In her articles, Frances Y. Kuo combines various disciplines, including Sobolev space and Rate of convergence.
Her Lattice research is multidisciplinary, incorporating elements of Function space and Hilbert space.
Her most cited work include:
- High-dimensional integration: The quasi-Monte Carlo way (400 citations)
- Remark on algorithm 659: Implementing Sobol's quasirandom sequence generator (205 citations)
- Constructing Sobol Sequences with Better Two-Dimensional Projections (182 citations)
What are the main themes of her work throughout her whole career to date?
Frances Y. Kuo mainly focuses on Quasi-Monte Carlo method, Applied mathematics, Discrete mathematics, Mathematical analysis and Lattice.
Her biological study spans a wide range of topics, including Monte Carlo integration, Statistical physics, Dynamic Monte Carlo method and Finite element method.
The concepts of her Applied mathematics study are interwoven with issues in Uncertainty quantification, Covariance, Covariance matrix, Elliptic partial differential equation and Random field.
Frances Y. Kuo has included themes like Combinatorics, Bounded function, Sobolev space, Function and Random variate in her Discrete mathematics study.
The various areas that Frances Y. Kuo examines in her Mathematical analysis study include Order, Log-normal distribution and Trigonometric functions.
Her research integrates issues of Numerical integration, Worst case error, Function space and Unit cube in her study of Lattice.
She most often published in these fields:
- Quasi-Monte Carlo method (37.69%)
- Applied mathematics (34.62%)
- Discrete mathematics (24.62%)
What were the highlights of her more recent work (between 2018-2021)?
- Applied mathematics (34.62%)
- Lattice (23.85%)
- Rate of convergence (20.00%)
In recent papers she was focusing on the following fields of study:
Her primary scientific interests are in Applied mathematics, Lattice, Rate of convergence, Random field and Algorithm.
Her Applied mathematics study combines topics in areas such as Uncertainty quantification, Quasi-Monte Carlo method, Series expansion and Trigonometric functions.
Her work deals with themes such as Bounded function and Finite element method, which intersect with Quasi-Monte Carlo method.
Her study in Lattice is interdisciplinary in nature, drawing from both Discrete mathematics and Computation.
Her Discrete mathematics research is multidisciplinary, incorporating perspectives in Upper and lower bounds, Random variate and Sobolev space.
Frances Y. Kuo has researched Random field in several fields, including Periodic function, Numerical analysis and Random variable.
Between 2018 and 2021, her most popular works were:
- Analysis of quasi-Monte Carlo methods for elliptic eigenvalue problems with stochastic coefficients (7 citations)
- A quasi-Monte Carlo Method for an Optimal Control Problem Under Uncertainty. (6 citations)
- Function integration, reconstruction and approximation using rank-$1$ lattices (3 citations)
In her most recent research, the most cited papers focused on:
- Mathematical analysis
- Statistics
- Algebra
Frances Y. Kuo focuses on Applied mathematics, Random field, Random variable, Rate of convergence and Quasi-Monte Carlo method.
Applied mathematics and Discrete cosine transform are two areas of study in which Frances Y. Kuo engages in interdisciplinary work.
Discrete cosine transform overlaps with fields such as Chebyshev filter, Lattice, General function, Function and Rank in her research.
Her Random variable research incorporates elements of Uncertainty quantification, Countable set, Numerical analysis and Spectral gap.
Throughout her Rate of convergence studies, Frances Y. Kuo incorporates elements of other sciences such as Sigma, Monte Carlo method, Gaussian quadrature, Discretization and Numerical integration.
Her Quasi-Monte Carlo method study combines topics in areas such as Eigenvalues and eigenvectors and Uniform boundedness.
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