Eric C. Cyr

Orcid: 0000-0003-3833-9598

According to our database1, Eric C. Cyr authored at least 42 papers between 2002 and 2024.

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Bibliography

2024
An implicit-in-time DPG formulation of the 1D1V Vlasov-Poisson equations.
Comput. Math. Appl., January, 2024

Gaussian Variational Schemes on Bounded and Unbounded Domains.
CoRR, 2024

DDU-Net: A Domain Decomposition-based CNN for High-Resolution Image Segmentation on Multiple GPUs.
CoRR, 2024

Spiking Physics-Informed Neural Networks on Loihi 2.
Proceedings of the Neuro Inspired Computational Elements Conference, 2024

2023
Graph Neural Networks and Applied Linear Algebra.
CoRR, 2023

A 2-Level Domain Decomposition Preconditioner for KKT Systems with Heat-Equation Constraints.
CoRR, 2023

2022
Thermodynamically consistent physics-informed neural networks for hyperbolic systems.
J. Comput. Phys., 2022

Neural-network based collision operators for the Boltzmann equation.
J. Comput. Phys., 2022

Parallel Training of GRU Networks with a Multi-Grid Solver for Long Sequences.
CoRR, 2022

Hierarchical partition of unity networks: fast multilevel training.
Proceedings of the Mathematical and Scientific Machine Learning, 2022

Parallel Training of GRU Networks with a Multi-Grid Solver for Long Sequences.
Proceedings of the Tenth International Conference on Learning Representations, 2022

2021
Monolithic Multigrid Methods for Magnetohydrodynamics.
SIAM J. Sci. Comput., 2021

Reduced Basis Approximations of Parameterized Dynamical Partial Differential Equations via Neural Networks.
CoRR, 2021

A Monolithic Algebraic Multigrid Framework for Multiphysics Applications with Examples from Resistive MHD.
CoRR, 2021

A Block Coordinate Descent Optimizer for Classification Problems Exploiting Convexity.
Proceedings of the AAAI 2021 Spring Symposium on Combining Artificial Intelligence and Machine Learning with Physical Sciences, Stanford, CA, USA, March 22nd - to, 2021

Partition of Unity Networks: Deep HP-Approximation.
Proceedings of the AAAI 2021 Spring Symposium on Combining Artificial Intelligence and Machine Learning with Physical Sciences, Stanford, CA, USA, March 22nd - to, 2021

2020
Layer-Parallel Training of Deep Residual Neural Networks.
SIAM J. Math. Data Sci., 2020

A linearity preserving nodal variation limiting algorithm for continuous Galerkin discretization of ideal MHD equations.
J. Comput. Phys., 2020

Regular sensitivity computation avoiding chaotic effects in particle-in-cell plasma methods.
J. Comput. Phys., 2020

A physics-informed operator regression framework for extracting data-driven continuum models.
CoRR, 2020

Monolithic Multigrid for Magnetohydrodynamics.
CoRR, 2020

Robust Training and Initialization of Deep Neural Networks: An Adaptive Basis Viewpoint.
Proceedings of Mathematical and Scientific Machine Learning, 2020

2019
IMEX and exact sequence discretization of the multi-fluid plasma model.
J. Comput. Phys., 2019

Multilevel Initialization for Layer-Parallel Deep Neural Network Training.
CoRR, 2019

2018
Scalable Preconditioners for Structure Preserving Discretizations of Maxwell Equations in First Order Form.
SIAM J. Sci. Comput., 2018

Performance of fully-coupled algebraic multigrid preconditioners for large-scale VMS resistive MHD.
J. Comput. Appl. Math., 2018

2016
Block Preconditioners for Stable Mixed Nodal and Edge finite element Representations of Incompressible Resistive MHD.
SIAM J. Sci. Comput., 2016

Teko: A Block Preconditioning Capability with Concrete Example Applications in Navier-Stokes and MHD.
SIAM J. Sci. Comput., 2016

Monolithic Multigrid Methods for Two-Dimensional Resistive Magnetohydrodynamics.
SIAM J. Sci. Comput., 2016

Stabilized FE simulation of prototype thermal-hydraulics problems with integrated adjoint-based capabilities.
J. Comput. Phys., 2016

2015
A new class of finite element variational multiscale turbulence models for incompressible magnetohydrodynamics.
J. Comput. Phys., 2015

2014
A Block Preconditioner for an Exact Penalty Formulation for Stationary MHD.
SIAM J. Sci. Comput., 2014

Approaches for Adjoint-Based A Posteriori Analysis of Stabilized Finite Element Methods.
SIAM J. Sci. Comput., 2014

Enhancing Least-Squares Finite Element Methods Through a Quantity-of-Interest.
SIAM J. Numer. Anal., 2014

Towards Extreme-Scale Simulations with Next-Generation Trilinos: A Low Mach Fluid Application Case Study.
Proceedings of the 2014 IEEE International Parallel & Distributed Processing Symposium Workshops, 2014

2013
A New Approximate Block Factorization Preconditioner for Two-Dimensional Incompressible (Reduced) Resistive MHD.
SIAM J. Sci. Comput., 2013

2012
Goal-Oriented Adaptivity and Multilevel Preconditioning for the Poisson-Boltzmann Equation.
J. Sci. Comput., 2012

Stabilization and scalable block preconditioning for the Navier-Stokes equations.
J. Comput. Phys., 2012

2010
A first-order system least-squares finite element method for the Poisson-Boltzmann equation.
J. Comput. Chem., 2010

2008
Numerical Methods for Computing the Free Energy of Coarse-Grained Molecular Systems
PhD thesis, 2008

2007
Using the method of weighted residuals to compute potentials of mean force.
J. Comput. Phys., 2007

2002
Using Design Patterns and XML to Construct an Extensible Finite Element System.
Proceedings of the Computational Science - ICCS 2002, 2002


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