672 citations · 1.4k across the 27 of their papers we have counts for
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Model reduction of dynamical systems on nonlinear manifolds using deep convolutional autoencoders
Kookjin Lee, Kevin Carlberg
Nearly all model-reduction techniques project the governing equations onto a linear subspace of the original state space. Such subspaces are typically computed using methods such a…
Recovering missing CFD data for high-order discretizations using deep neural networks and dynamics learning
Kevin T. Carlberg, Antony Jameson, Mykel J. Kochenderfer +3
Data I/O poses a significant bottleneck in large-scale CFD simulations; thus, practitioners would like to significantly reduce the number of times the solution is saved to disk, ye…
An efficient, globally convergent method for optimization under uncertainty using adaptive model reduction and sparse grids
Matthew J. Zahr, Kevin T. Carlberg, Drew P. Kouri
This work introduces a new method to efficiently solve optimization problems constrained by partial differential equations (PDEs) with uncertain coefficients. The method leverages…
Machine-learning error models for approximate solutions to parameterized systems of nonlinear equations
Brian A. Freno, Kevin T. Carlberg
This work proposes a machine-learning framework for constructing statistical models of errors incurred by approximate solutions to parameterized systems of nonlinear equations. The…