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Publication	Type	Year
A Two-Level Scheme for Training Partition of Unity Networks 27th International Domain Decomposition Conference Eric Christopher Cyr, Nathaniel Albert Trask, Amelia Henriksen, Carianne Martinez	Conference Presentation – 2022 Conference Presentation	2022
A DPG Space-Time Vlasov-Poisson Discretization with Adaptive Mesh Refinement SIAM Annual Nathan V. Roberts, Stephen D Bond, Eric Christopher Cyr	Conference Presentation – 2022 Conference Presentation	2022
Neural-Network Based Collision Operators for the Boltzmann Equation SIAM Annual Meeting 2022 Eric Christopher Cyr, Nathan V. Roberts, Stephen D Bond, Sean (AMD) Miller	Conference Presentation – 2022 Conference Presentation	2022
Preconditioners for Plasma Physics and Magnetohydrodynamics: Handling Multiple Timescales Preconditioning 2022International Conference on Preconditioning Techniques for Scientific and Industrial Applications Eric Christopher Cyr, John N. Shadid, Raymond S. Tuminaro	Conference Presentation – 2022 Conference Presentation	2022
Parallel-In-Time Training of Recurrent Neural Networks Copper Mountain Conference on Iterative Methods Eric Christopher Cyr, Gordon (KAU) Moon	Conference Presentation – 2022 Conference Presentation	2022
Learning an Algebriac Multrigrid Interpolation Operator Using a Modified GraphNet Architecture Nicholas S. Moore (Texas Tech University), Eric Christopher Cyr, Christopher Siefert https://www.osti.gov/search/identifier:1859673	SAND Report – 2022 SAND Report	2022
Coupling Kinetic PIC to Multi-Fluid Plasma Models using Compatible Discretizations SIAM Parallel Processing 2022 Eric Christopher Cyr	Conference Presentation – 2022 Conference Presentation	2022
A DPG Space-Time Vlasov-Poisson Discretization with Adaptive Mesh Refinement SIAM Annual Nathan V. Roberts, Stephen D Bond, Eric Christopher Cyr	Abstract – 2022 Abstract	2022
Parallel Training of GRU Networks with a Multi-Grid Solver for Long Sequences The Tenth International Conference on Learning Representations Gordon Euhyun Moon (KAU), Eric Christopher Cyr	Conference Paper – 2022 Conference Paper	2022
A Monolithic Algebraic Multigrid Framework for Multiphysics Applications with Examples from Resistive MHD Electronic Transactions on Numerical Analysis Peter Brian Ohm, Jonathan J. Hu, John N. Shadid, Eric Christopher Cyr, Raymond S. Tuminaro, Tobias A. Wiesner	Journal Article – 2022 Journal Article	2022
Machine learning and spatial decomposition for large CT scans IS&T Electronic Imaging 2022 Eric Christopher Cyr, Gary Joseph Saavedra	Conference Presentation – 2021 Conference Presentation	2021
The ASC Advanced Machine Learning Initiative at Sandia National Laboratories: FY21 Accomplishments and FY22 Plans ASC AMLI Program Review Ron A. Oldfield, Sharlotte LorraineBolyard Kramer, Ahmad Rushdi, Erin Acquesta, John M Emery, Paul Allen Kuberry, Jaideep Ray, Sarah Ackerman, Eric Christopher Cyr, Gary Joseph Saavedra, Clayton Hughes, Suma George Cardwell, John Darby Smith	Presentation (non-conference) – 2021 Presentation (non-conference)	2021
A Layer-Parallel Approach for Training Deep Neural Networks Mathematical Foundations and Applications of Deep Learning Eric Christopher Cyr, Stefanie Guenther (LLNL), Lars Ruthotto (Emory), Jacob B. Schroder (UNM), Nico R. Gauger (TU Kaiserslautern), Gordon Moon (KAU), Ravi Ghanshyam Patel	Conference Presentation – 2021 Conference Presentation	2021
Modal Operator Regression for Extracting Nonlocal Continuum Models Usnccm16 Ravi Ghanshyam Patel, Nathaniel Albert Trask, Mitchell Wood, Eric Christopher Cyr	Conference Presentation – 2021 Conference Presentation	2021
Perfection is the Enemy of Fast: The Case for Mathematically Induced Parallelism Computer Science Research Institute throughout our Summer Seminar Series Eric Christopher Cyr	Presentation (non-conference) – 2021 Presentation (non-conference)	2021
A Layer-Parallel Approach for Training Deep Neural Networks Fomics-dadsi Seminars On Scientific Learning Eric Christopher Cyr, Stefanie Guenther (LLNL), Lars Ruthotto (Emory), Jacob B. Schroder (UNM), Nico R. Gauger (TU Kaiserslautern), Gordon Moon (KAU), Ravi Ghanshyam Patel https://www.osti.gov/search/identifier:1872882	Presentation (non-conference) – 2021 Presentation (non-conference)	2021
An Adaptive Basis Perspective to Improve Initialization and Accelerate Training of DNNs Fomics-dadsi Seminars On Scientific Learning Eric Christopher Cyr, Mamikon Gulian, Kookjin Lee (ASU), Ravi Ghanshyam Patel, Mauro Perego, Nathaniel Albert Trask https://www.osti.gov/search/identifier:1872708	Presentation (non-conference) – 2021 Presentation (non-conference)	2021
An Algebraic Monolithic Method for Volume-coupled Multiphysics Problems The 9th ediiton of the International Conference on Computational Methods for Coupled Problems in Science and Engineering Peter Brian Ohm, Raymond S. Tuminaro, Jonathan J. Hu, John N. Shadid, Eric Christopher Cyr, Tobias Wiesner https://www.osti.gov/search/identifier:1872519	Conference Presentation – 2021 Conference Presentation	2021
Multiscale training for Physics-informed Neural Networks Copper Mountain Conference On Multigrid Methods Ravi Ghanshyam Patel, Nathaniel Albert Trask, Eric Christopher Cyr https://www.osti.gov/search/identifier:1861255	Conference Presentation – 2021 Conference Presentation	2021
A Monolithic Algebraic Multigrid Approach for Coupled Multiphysics Problems using the MueLu Framework Cm202120th Copper Mountain Conference On Multigrid Methods Peter Brian Ohm, Raymond S. Tuminaro, John N. Shadid, Jonathan J. Hu, Tobias Wiesner, Eric Christopher Cyr https://www.osti.gov/search/identifier:1861027	Conference Presentation – 2021 Conference Presentation	2021
Training Deep Neural Networks using Layer-Parallelism CIS EAB Review Eric Christopher Cyr	Presentation (non-conference) – 2021 Presentation (non-conference)	2021
A block coordinate descent optimizer for classification problems exploiting convexity Aaai-mlps 2021 Mamikon Gulian, Ravi Ghanshyam Patel, Nathaniel Albert Trask, Eric Christopher Cyr https://www.osti.gov/search/identifier:1855748	Conference Paper – 2021 Conference Paper	2021
EMPIRE-PIC: A Performance Portable Unstructured Particle-in-Cell Code Communications in Computational Physics Matthew Tyler Bettencourt, Dominic A. S. Brown, Keith L. Cartwright1, Eric Christopher Cyr, Christian Alexander Glusa, Paul T. Lin, Stan Gerald Moore, Duncan A. O. McGregor, Roger P. Pawlowski, Edward Geoffrey Phillips, Nathan V. Roberts, Steven A. Wright, Satheesh Maheswaran, John P. Jones, Stephen A. Jarvis https://www.osti.gov/search/identifier:1822232	Journal Article – 2021 Journal Article	2021
A Physics-Informed Operator Regression Framework for Extracting Data-Driven Continuum Models Siam Cse21 Ravi Ghanshyam Patel, Nathaniel Albert Trask, Mitchell Wood, Eric Christopher Cyr https://www.osti.gov/search/identifier:1853856	Conference Presentation – 2021 Conference Presentation	2021
Thermodynamically consistent physics-informed neural networks for hyperbolic systems SIAM Conference on Computational Science and Engineering Indu Manickam, Ravi Ghanshyam Patel, Nathaniel Albert Trask, Mitchell Wood, Myoungkyu NMN Lee, Ignacio Tomas, Eric Christopher Cyr https://www.osti.gov/search/identifier:1847572	Conference Presentation – 2021 Conference Presentation	2021
Document Title	Type	Year

Results 1–25 of 243

Publications

A Two-Level Scheme for Training Partition of Unity Networks

A DPG Space-Time Vlasov-Poisson Discretization with Adaptive Mesh Refinement

Neural-Network Based Collision Operators for the Boltzmann Equation

Preconditioners for Plasma Physics and Magnetohydrodynamics: Handling Multiple Timescales

Parallel-In-Time Training of Recurrent Neural Networks

Learning an Algebriac Multrigrid Interpolation Operator Using a Modified GraphNet Architecture

Coupling Kinetic PIC to Multi-Fluid Plasma Models using Compatible Discretizations

A DPG Space-Time Vlasov-Poisson Discretization with Adaptive Mesh Refinement

Parallel Training of GRU Networks with a Multi-Grid Solver for Long Sequences

A Monolithic Algebraic Multigrid Framework for Multiphysics Applications with Examples from Resistive MHD

Machine learning and spatial decomposition for large CT scans

The ASC Advanced Machine Learning Initiative at Sandia National Laboratories: FY21 Accomplishments and FY22 Plans

A Layer-Parallel Approach for Training Deep Neural Networks

Modal Operator Regression for Extracting Nonlocal Continuum Models

Perfection is the Enemy of Fast: The Case for Mathematically Induced Parallelism

A Layer-Parallel Approach for Training Deep Neural Networks

An Adaptive Basis Perspective to Improve Initialization and Accelerate Training of DNNs

An Algebraic Monolithic Method for Volume-coupled Multiphysics Problems

Multiscale training for Physics-informed Neural Networks

A Monolithic Algebraic Multigrid Approach for Coupled Multiphysics Problems using the MueLu Framework

Training Deep Neural Networks using Layer-Parallelism

A block coordinate descent optimizer for classification problems exploiting convexity

EMPIRE-PIC: A Performance Portable Unstructured Particle-in-Cell Code

A Physics-Informed Operator Regression Framework for Extracting Data-Driven Continuum Models

Thermodynamically consistent physics-informed neural networks for hyperbolic systems