196 citations · 296 across the 12 of their papers we have counts for
6 papers · 1 filter
Efficient Computation of Tucker Decomposition for Streaming Scientific Data Compression
Saibal De, Zitong Li, Hemanth Kolla +1
The Tucker decomposition, an extension of singular value decomposition for higher-order tensors, is a useful tool in analysis and compression of large-scale scientific data. While…
Streaming Generalized Canonical Polyadic Tensor Decompositions
Eric Phipps, Nick Johnson, Tamara G. Kolda
In this paper, we develop a method which we call OnlineGCP for computing the Generalized Canonical Polyadic (GCP) tensor decomposition of streaming data. GCP differs from tradition…
Solvers and precondtioners based on Gauss-Seidel and Jacobi algorithms for non-symmetric stochastic Galerkin system of equations
Ramakrishna Tipireddy, Eric T. Phipps, Roger G. Ghanem
In this work, solvers and preconditioners based on Gauss-Seidel and Jacobi algorithms are explored for stochastic Galerkin discretization of partial differential equations (PDEs) w…
Hierarchical Schur complement preconditioner for the stochastic Galerkin finite element methods
Bedřich Sousedík, Roger G. Ghanem, Eric T. Phipps
Use of the stochastic Galerkin finite element methods leads to large systems of linear equations obtained by the discretization of tensor product solution spaces along their spatia…
A Lanczos Method for Approximating Composite Functions
Paul G. Constantine, Eric T. Phipps
We seek to approximate a composite function h(x) = g(f(x)) with a global polynomial. The standard approach chooses points x in the domain of f and computes h(x) at each point, whic…
Sparse Pseudospectral Approximation Method
Paul G. Constantine, Michael S. Eldred, Eric T. Phipps
Multivariate global polynomial approximations - such as polynomial chaos or stochastic collocation methods - are now in widespread use for sensitivity analysis and uncertainty quan…