4 citations · 9 across the 8 of their papers we have counts for
5 papers · 1 filter
Lookahead data-gathering strategies for online adaptive model reduction of transport-dominated problems
Rodrigo Singh, Wayne Isaac Tan Uy, Benjamin Peherstorfer
Online adaptive model reduction efficiently reduces numerical models of transport-dominated problems by updating reduced spaces over time, which leads to nonlinear approximations o…
Reduced models with nonlinear approximations of latent dynamics for model premixed flame problems
Wayne Isaac Tan Uy, Christopher R. Wentland, Cheng Huang +1
Efficiently reducing models of chemically reacting flows is often challenging because their characteristic features such as sharp gradients in the flow fields and couplings over va…
Probabilistic error estimation for non-intrusive reduced models learned from data of systems governed by linear parabolic partial differential equations
Wayne Isaac Tan Uy, Benjamin Peherstorfer
This work derives a residual-based a posteriori error estimator for reduced models learned with non-intrusive model reduction from data of high-dimensional systems governed by line…
Neural network representation of the probability density function of diffusion processes
Wayne Isaac Tan Uy, Mircea Grigoriu
Physics-informed neural networks are developed to characterize the state of dynamical systems in a random environment. The neural network approximates the probability density funct…
Specification of additional information for solving stochastic inverse problems
Wayne Isaac T. Uy, Mircea D. Grigoriu
Methods have been developed to identify the probability distribution of a random vector from information consisting of its bounded range and the probability density function or…