49 citations · 102 across the 11 of their papers we have counts for
6 papers · 1 filter
GP-HMAT: Scalable, Gaussian Process Regression with Hierarchical Low-Rank Matrices
Vahid Keshavarzzadeh, Shandian Zhe, Robert M. Kirby +1
A Gaussian process (GP) is a powerful and widely used regression technique. The main building block of a GP regression is the covariance kernel, which characterizes the relationshi…
A bandit-learning approach to multifidelity approximation
Yiming Xu, Vahid Keshavarzzadeh, Robert M. Kirby +1
Multifidelity approximation is an important technique in scientific computation and simulation. In this paper, we introduce a bandit-learning approach for leveraging data of varyin…
Parametric Topology Optimization with Multi-Resolution Finite Element Models
Vahid Keshavarzzadeh, Robert M. Kirby, Akil Narayan
We present a methodical procedure for topology optimization under uncertainty with multi-resolution finite element models. We use our framework in a bi-fidelity setting where a coa…
Generation of Nested Quadrature Rules for Generic Weight Functions via Numerical Optimization: Application to Sparse Grids
Vahid Keshavarzzadeh, Robert M. Kirby, Akil Narayan
We present a numerical framework for computing nested quadrature rules for various weight functions. The well-known Kronrod method extends the Gauss-Legendre quadrature by adding n…
Convergence Acceleration for Time Dependent Parametric Multifidelity Models
Vahid Keshavarzzadeh, Robert M. Kirby, Akil Narayan
We present a numerical method for convergence acceleration for multifidelity models of parameterized ordinary differential equations. The hierarchy of models is defined as trajecto…
Numerical Integration in Multiple Dimensions with Designed Quadrature
Vahid Keshavarzzadeh, Robert M. Kirby, Akil Narayan
We present a systematic computational framework for generating positive quadrature rules in multiple dimensions on general geometries. A direct moment-matching formulation that enf…