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Publication	Type	Year
An Adaptive Basis Perspective to Improve Initialization and Accelerate Training of DNNs SIAM Conference on Computational Science and Engineering (CSE21) Eric Christopher Cyr, Mamikon Gulian, Ravi Ghanshyam Patel, Mauro Perego, Nathaniel Albert Trask https://www.osti.gov/search/identifier:1847582	Conference Presentation – 2021 Conference Presentation	2021
Model Parallelism with Spatial Decomposition of Volumetric Data for Deep Learning SIAM Computational Science and Engineering 2021 Gary Joseph Saavedra, Eric Christopher Cyr, Jacob Schroder, Russell Hewett https://www.osti.gov/search/identifier:1847461	Conference Presentation – 2021 Conference Presentation	2021
An Algebraic Monolithic Method for Volume-coupled Multiphysics Problems IX International Conference on Coupled Problems in Science and Engineering Peter Brian Ohm, Raymond S. Tuminaro, Jonathan J. Hu, John N. Shadid, Eric Christopher Cyr, Tobias Wiesner	Abstract – 2021 Abstract	2021
Towards Predictive Plasma Science and Engineering through Revolutionary Multi-Scale Algorithms and Models, Final Report George Russell Laity, Allen C. Robinson, Michael E. Cuneo, Mary Kathleen Alam, Kristian Beckwith, Nichelle Lee Bennett, Matthew Tyler Bettencourt, Stephen D Bond, Kyle Cochrane, Louise Criscenti, Eric Christopher Cyr, Karen June De Zetter, Richard R. Drake, Evstati Georgiev Evstatiev, Andrew Steven Fierro, Thomas Anthony Gardiner, Forrest Glines, Ronald S. Goeke, Nathaniel Donald Hamlin, Russell Hooper, Jason Koski, James Matthew Doyle Lane, Steven Robert Larson, Kevin Leung, Duncan Alisdair Odum McGregor, Philip Rocco Miller, Sean Miller, Susan Jasmin Ossareh, Edward Geoffrey Phillips, Sean Simpson, David Sirajuddin, Thomas M. Smith, Matthew Scot Swan, Aidan P. Thompson, Julien Guy Tranchida, Asa Jal Bortz-Johnson, Dale Robert Welch, Alex Moore Russell, Eric Duarte Watson, David Vincent Rose, Ryan D McBride https://www.osti.gov/search/identifier:1813907	SAND Report – 2021 SAND Report	2021
Partition of unity networks: data-driven meshfree hp-approximation AAAI 2021 Spring Symposium on Combining Artificial Intelligence and Machine Learning with Physics Sciences Lee Kookjin, Nathaniel Albert Trask, Ravi Ghanshyam Patel, Mamikon Gulian, Eric Christopher Cyr https://www.osti.gov/search/identifier:1835970	Conference Paper – 2020 Conference Paper	2020
Learning continuum-scale models from micro-scale dynamics via Operator Regression 14th World Congress in Computational Mechanics Ravi Ghanshyam Patel, Nathaniel Albert Trask, Mitchell Wood, Eric Christopher Cyr https://www.osti.gov/search/identifier:1834283	Conference Presentation – 2020 Conference Presentation	2020
Finite Element Tools for Performance Portability of Implicit and IMEX Simulations on Next Generation Architectures 14th World Congress on Computational Mechanics (Virtual meeting) Roger P. Pawlowski, Eric T. Phipps, Christian Robert Trott, Eric Christopher Cyr, John N. Shadid https://www.osti.gov/search/identifier:1833498	Conference Presentation – 2020 Conference Presentation	2020
TorchBraid Eric Christopher Cyr	Marketing or Promotional – 2020 Marketing or Promotional	2020
A Layer-Parallel Approach for Training Deep Neural Networks George Mason University - CMAI Colloquium Eric Christopher Cyr, Stefanie Guenther (LLNL), Lars (Emory) Ruthotto, Jacob B. Schroder (UNM), Nico R. Gauger (TU Kaiserslautern), Denis Ridzal https://www.osti.gov/search/identifier:1812174	Presentation (non-conference) – 2020 Presentation (non-conference)	2020
Machine Learning for Accelerating Direct-Simulation Monte-Carlo Collision Operators Sandia Machine Learning and Deep Learning Workshop Sean Miller, Nathan V. Roberts, Eric Christopher Cyr https://www.osti.gov/search/identifier:1811433	Conference Paper – 2020 Conference Paper	2020
Robust Training and Initialization of Deep Neural Networks An Adaptive Basis Viewpoint Princeton MSML meeting Eric Christopher Cyr, Mamikon Gulian, Ravi Ghanshyam Patel, Mauro Perego, Nathaniel Albert Trask https://www.osti.gov/search/identifier:1810691	Conference Paper – 2020 Conference Paper	2020
Robust training and initialization of deep neural networks: an adaptive basis viewpoint 2020 Siam-caims An20 Mamikon Gulian, Eric Christopher Cyr, Ravi Ghanshyam Patel, Mauro Perego, Nathaniel Albert Trask https://www.osti.gov/search/identifier:1808257	Conference Paper – 2020 Conference Paper	2020
Advancing Fusion with Machine Learning Research Needs Workshop Report Journal of Fusion Energy D. Humphreys, M.D. Boyer A. Kupresanin, J. Canik, C.S. Chang, Eric Christopher Cyr, R. Granetz, J. Hittinger, E. Kolemen, E. Lawrence, V. Pascucci, A. Patra, D. Schissel https://www.osti.gov/search/identifier:1670184	Journal Article – 2020 Journal Article	2020
Layer-Parallel Training: Nested Iteration SIAM MDS (Virtual Mini) Eric Christopher Cyr, Stefanie (LLNL) Guenther, Lars (Emory) Ruthotto, Jacob B. (UNM) Schroder, Nico R. (TU Kaiserslautern) Gauger https://www.osti.gov/search/identifier:1807445	Conference Paper – 2020 Conference Paper	2020
A block coordinate descent optimizer for classification problems exploiting convexity Arxiv Ravi Ghanshyam Patel, Nathaniel Albert Trask, Mamikon Gulian, Eric Christopher Cyr https://www.osti.gov/search/identifier:1834091	Journal Article – 2020 Journal Article	2020
A physics-informed operator regression framework for extracting data-driven continuum models Arxiv Ravi Ghanshyam Patel, Nathaniel Albert Trask, Mitchell Wood, Eric Christopher Cyr https://www.osti.gov/search/identifier:1725869	Journal Article – 2020 Journal Article	2020
A Plasma Modeling Hierarchy and Verification Approach Richard Michael Jack Kramer, Eric Christopher Cyr, Sean Miller, Edward Geoffrey Phillips, Gregg Arthur Radtke, Allen C. Robinson, John N. Shadid https://www.osti.gov/search/identifier:1608511	SAND Report – 2020 SAND Report	2020
Solving The Multiscale Modeling Problem Of Plasma Physics With Hetrogeneous Methods wccm Matthew Tyler Bettencourt, Eric Christopher Cyr, Edward Geoffrey Phillips, Kristian Beckwith, Keith Cartwright, Duncan Alisdair Odum McGregor, Sean Miller, Nathan V. Roberts, Nicholas Roberds, Roger P. Pawlowski, David Sirajuddin	Abstract – 2020 Abstract	2020
Discretization of the Multi-fluid Plasma Model using IMEX and Mixed Continuous/Discontinuous FEM The 44th SIAM Southeastern Atlantic Section Conference Sean Miller, Eric Christopher Cyr, Edward Geoffrey Phillips, Roger P. Pawlowski, Kristian Beckwith, Matthew Tyler Bettencourt, Keith Cartwright, Sidney Shields https://www.osti.gov/search/identifier:1770844	Conference Paper – 2020 Conference Paper	2020
A Layer-Parallel Approach for Training Deep Neural Networks SIAM Parallel Processing Eric Christopher Cyr, Stefanie Guenther (LLNL), Lars Ruthotto (Emory), Jacob B. Schroder (UNM), Nico R. Gauger (TU Kaiserslautern) https://www.osti.gov/search/identifier:1766945	Conference Paper – 2020 Conference Paper	2020
Discretization of the Multi-fluid Plasma Model using IMEX and Mixed Continuous/Discontinuous FEM The 44th SIAM Southeastern Atlantic Section Conference Sean Miller, Eric Christopher Cyr, Edward Geoffrey Phillips, Roger P. Pawlowski, Kristian Beckwith, Matthew Tyler Bettencourt, Keith Cartwright, Sidney Shields	Abstract – 2020 Abstract	2020
Enabling 5G Distributed Scientific Data Analysis through Hierarchical Architectures and Algorithms 5G Enabled Energy Innovation Workshop (5GEEIW) Eric Christopher Cyr https://www.osti.gov/search/identifier:1765641	Conference Paper – 2020 Conference Paper	2020
Discretization of the Multi-fluid Plasma Model using IMEX and Mixed Continuous/Discontinuous FEM 16th Copper Mountain Conference On Iterative Methods Sean Miller, Eric Christopher Cyr, Edward Geoffrey Phillips	Abstract – 2020 Abstract	2020
Power-flow Simulation Enabled By Numerical Methods For Multi-scale Relativistic Plasmas International Conference on Computational Methods for Coupled Problems in Science and Engineering (WCCM XIV and ECCOMAS2020) Kristian Beckwith, Thomas Anthony Gardiner, Matthew Tyler Bettencourt, Forrest Glines, Keith Cartwright, Eric Christopher Cyr, Sean Miller, Edward Geoffrey Phillips, Nathan V. Roberts, Roger P. Pawlowski, David Sirajuddin	Abstract – 2020 Abstract	2020
Improved Neural Network Training: Layer-Parallelism, Least-squares and Initialization International Workshop On Scientific Machine Learning Eric Christopher Cyr, Mamikon Gulian, Ravi Ghanshyam Patel, Mauro Perego, Nathaniel Albert Trask, Denis Ridzal, Stefanie Guenther (LLNL), Lars Ruthotto (Emory), Jacob B. Schroder (UNM), Nico R. Gauger (TU Kaiserslautern) https://www.osti.gov/search/identifier:1643364	Conference Paper – 2019 Conference Paper	2019
Document Title	Type	Year

Results 26–50 of 243

Publications

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

Model Parallelism with Spatial Decomposition of Volumetric Data for Deep Learning

An Algebraic Monolithic Method for Volume-coupled Multiphysics Problems

Towards Predictive Plasma Science and Engineering through Revolutionary Multi-Scale Algorithms and Models, Final Report

Partition of unity networks: data-driven meshfree hp-approximation

Learning continuum-scale models from micro-scale dynamics via Operator Regression

Finite Element Tools for Performance Portability of Implicit and IMEX Simulations on Next Generation Architectures

TorchBraid

A Layer-Parallel Approach for Training Deep Neural Networks

Machine Learning for Accelerating Direct-Simulation Monte-Carlo Collision Operators

Robust Training and Initialization of Deep Neural Networks An Adaptive Basis Viewpoint

Robust training and initialization of deep neural networks: an adaptive basis viewpoint

Advancing Fusion with Machine Learning Research Needs Workshop Report

Layer-Parallel Training: Nested Iteration

A block coordinate descent optimizer for classification problems exploiting convexity

A physics-informed operator regression framework for extracting data-driven continuum models

A Plasma Modeling Hierarchy and Verification Approach

Solving The Multiscale Modeling Problem Of Plasma Physics With Hetrogeneous Methods

Discretization of the Multi-fluid Plasma Model using IMEX and Mixed Continuous/Discontinuous FEM

A Layer-Parallel Approach for Training Deep Neural Networks

Discretization of the Multi-fluid Plasma Model using IMEX and Mixed Continuous/Discontinuous FEM

Enabling 5G Distributed Scientific Data Analysis through Hierarchical Architectures and Algorithms

Discretization of the Multi-fluid Plasma Model using IMEX and Mixed Continuous/Discontinuous FEM

Power-flow Simulation Enabled By Numerical Methods For Multi-scale Relativistic Plasmas

Improved Neural Network Training: Layer-Parallelism, Least-squares and Initialization