His primary scientific interests are in Mathematical analysis, Convolution, Algorithm, Vibration and Applied mathematics. His study involves Finite difference, Singularity, Numerical analysis and Subspace topology, a branch of Mathematical analysis. The study incorporates disciplines such as Heteroclinic orbit, Field, Beam, Singular solution and Bistability in addition to Convolution.
Guo-Wei Wei has included themes like Multiresolution analysis, Partial differential equation, Numerical stability, Mathematical optimization and Wavelet in his Algorithm study. The various areas that Guo-Wei Wei examines in his Vibration study include Geometry, Boundary value problem and Robustness. His Applied mathematics study combines topics from a wide range of disciplines, such as Computer simulation, Benchmark, Nonlinear system, Eigenvalues and eigenvectors and Dirichlet distribution.
The scientist’s investigation covers issues in Mathematical analysis, Statistical physics, Algorithm, Persistent homology and Convolution. The concepts of his Mathematical analysis study are interwoven with issues in Geometry and Wavelet. His work carried out in the field of Statistical physics brings together such families of science as Molecular dynamics, Solvation, Poisson–Boltzmann equation, Variational principle and Differential geometry.
His Algorithm study frequently draws connections to adjacent fields such as Partial differential equation. In his research on the topic of Persistent homology, Graph theory is strongly related with Artificial intelligence. Guo-Wei Wei combines subjects such as Spectral method and Applied mathematics with his study of Convolution.
His primary areas of investigation include Artificial intelligence, Severe acute respiratory syndrome coronavirus 2, Machine learning, Persistent homology and Genome. His study focuses on the intersection of Artificial intelligence and fields such as Graph theory with connections in the field of Structure and Virtual screening. His Persistent homology research is included under the broader classification of Topology.
His study in Topology is interdisciplinary in nature, drawing from both Graph and Representation. His Deep learning study integrates concerns from other disciplines, such as Artificial neural network and Algorithm. His work in Algorithm is not limited to one particular discipline; it also encompasses Differential geometry.
Guo-Wei Wei mostly deals with Artificial intelligence, Severe acute respiratory syndrome coronavirus 2, Genotyping, Graph theory and Deep learning. His Artificial intelligence research incorporates elements of Topology and Machine learning. His work deals with themes such as Virtual screening and Differential geometry, which intersect with Graph theory.
His Deep learning research is multidisciplinary, incorporating perspectives in Algorithm, Persistent homology, Convolutional neural network and Algebraic topology. In his papers, Guo-Wei Wei integrates diverse fields, such as Algorithm and Estimator. His Persistent homology research includes themes of Eigenvalues and eigenvectors, Statistical physics, Graph and Laplace operator.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Improvements to the APBS biomolecular solvation software suite.
Elizabeth Jurrus;Dave Engel;Keith Star;Kyle Monson.
Protein Science (2018)
High order matched interface and boundary method for elliptic equations with discontinuous coefficients and singular sources
Y. C. Zhou;Shan Zhao;Michael Feig;G. W. Wei.
Journal of Computational Physics (2006)
A NEW BENCHMARK QUALITY SOLUTION FOR THE BUOYANCY-DRIVEN CAVITY BY DISCRETE SINGULAR CONVOLUTION
D. C. Wan;B. S. V. Patnaik;G. W. Wei.
Numerical Heat Transfer Part B-fundamentals (2001)
Discrete singular convolution for the solution of the Fokker–Planck equation
G. W. Wei.
Journal of Chemical Physics (1999)
Methods for performing DAF data filtering and padding
Donald J. Kouri;David K. Hoffman;Ioannis Kakadiaris;Zhuoer Shi.
Discrete singular convolution and its application to the analysis of plates with internal supports. Part 1: Theory and algorithm
G. W Wei;G. W Wei;Y. B Zhao;Yang Xiang.
International Journal for Numerical Methods in Engineering (2002)
Generalized Perona-Malik equation for image restoration
IEEE Signal Processing Letters (1999)
A new algorithm for solving some mechanical problems
Computer Methods in Applied Mechanics and Engineering (2001)
VIBRATION ANALYSIS BY DISCRETE SINGULAR CONVOLUTION
Journal of Sound and Vibration (2001)
High-order FDTD methods via derivative matching for Maxwell's equations with material interfaces
Shan Zhao;G. W. Wei.
Journal of Computational Physics (2004)
International Journal for Numerical Methods in Biomedical Engineering
(Impact Factor: 2.648)
Profile was last updated on December 6th, 2021.
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