1 citations · 2 across the 5 of their papers we have counts for
7 papers
ResGene-T: A Tensor-Based Residual Network Approach for Genomic Prediction
Kuldeep Pathak, Kapil Ahuja, Eric de Sturler
In this work, we propose a new deep learning model for Genomic Prediction (GP), which involves correlating genotypic data with phenotypic. The genotypes are typically fed as a sequ…
An Adaptive Mixed Precision and Dynamically Scaled Preconditioned Conjugate Gradient Algorithm
Yichen Guo, Eric de Sturler, Tim Warburton
We propose an adaptive mixed precision and dynamically scaled preconditioned conjugate gradient algorithm (AMP-PCG). It dynamically adjusts the precision for storing vectors and co…
Krylov Subspace Recycling for Evolving Structures
Matthias Bolten, Eric de Sturler, Camilla Hahn
Krylov subspace recycling is a powerful tool for solving long series of large, sparse linear systems that change slowly. In PDE constrained shape optimization, these appear natural…
Randomization for the Efficient Computation of Parametric Reduced Order Models for Inversion
Selin Aslan, Eric de Sturler, Serkan Gugercin
Nonlinear parametric inverse problems appear in many applications. Here, we focus on diffuse optical tomography (DOT) in medical imaging to recover unknown images of interest, such…
Robust Parameter Inversion using Adaptive Reduced Order Models
Drayton Munster, Eric de Sturler
Nonlinear parametric inverse problems appear in many applications and are typically very expensive to solve, especially if they involve many measurements. These problems pose huge…
A survey of subspace recycling iterative methods
Kirk M. Soodhalter, Eric de Sturler, Misha Kilmer
This survey concerns subspace recycling methods, a popular class of iterative methods that enable effective reuse of subspace information in order to speed up convergence and find…