10 citations · 17 across the 3 of their papers we have counts for
4 papers
Bi-fidelity Modeling of Uncertain and Partially Unknown Systems using DeepONets
Subhayan De, Matthew Reynolds, Malik Hassanaly +2
Recent advances in modeling large-scale complex physical systems have shifted research focuses towards data-driven techniques. However, generating datasets by simulating complex sy…
On transfer learning of neural networks using bi-fidelity data for uncertainty propagation
Subhayan De, Jolene Britton, Matthew Reynolds +3
Due to their high degree of expressiveness, neural networks have recently been used as surrogate models for mapping inputs of an engineering system to outputs of interest. Once tra…
Optimization via Separated Representations and the Canonical Tensor Decomposition
Matthew J Reynolds, Gregory Beylkin, Alireza Doostan
We introduce a new, quadratically convergent algorithm for finding maximum absolute value entries of tensors represented in the canonical format. The computational complexity of th…
Randomized Alternating Least Squares for Canonical Tensor Decompositions: Application to a PDE with Random Data
Matthew Reynolds, Alireza Doostan, Gregory Beylkin
This paper introduces a randomized variation of the alternating least squares (ALS) algorithm for rank reduction of canonical tensor formats. The aim is to address the potential nu…