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05/08/2023
A 2-Level Domain Decomposition Preconditioner for KKT Systems with Heat-Equation Constraints
Solving optimization problems with transient PDE-constraints is computat...
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03/07/2022
Parallel Training of GRU Networks with a Multi-Grid Solver for Long Sequences
Parallelizing Gated Recurrent Unit (GRU) networks is a challenging task,...
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10/20/2021
Reduced Basis Approximations of Parameterized Dynamical Partial Differential Equations via Neural Networks
Projection-based reduced order models are effective at approximating par...
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03/12/2021
A Monolithic Algebraic Multigrid Framework for Multiphysics Applications with Examples from Resistive MHD
A multigrid framework is described for multiphysics applications. The fr...
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01/27/2021
Partition of unity networks: deep hp-approximation
Approximation theorists have established best-in-class optimal approxima...
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12/09/2020
Thermodynamically consistent physics-informed neural networks for hyperbolic systems
Physics-informed neural network architectures have emerged as a powerful...
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09/25/2020
A physics-informed operator regression framework for extracting data-driven continuum models
The application of deep learning toward discovery of data-driven models ...
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06/17/2020
A block coordinate descent optimizer for classification problems exploiting convexity
Second-order optimizers hold intriguing potential for deep learning, but...
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12/19/2019
Multilevel Initialization for Layer-Parallel Deep Neural Network Training
This paper investigates multilevel initialization strategies for trainin...
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12/10/2019