Publications

Results 1–25 of 32
Date Inputs. Currently set to enter a start and end date.
Current Filters Clear all
  • Remove author filter×
Publication Type Year

Identifying Governing ODEs in Irregular Physical Domain with Diffusion

64th Annual Meeting of the APS Division of Plasma Physics

Gina Rose Vasey, Kristian Beckwith, Patrick Knapp, William Lewis, Brian O'Shea, Andrew Christlieb, Ravi Ghanshyam Patel, Christopher Ashley Jennings

Abstract – 2022 Abstract 2022

An autoencoder based reduced order model of low density plasma for optimal experimental design

APS Division of Plasma Physics

Ravi Ghanshyam Patel, William Lewis, Patrick Knapp

Abstract – 2022 Abstract 2022

Continuum semiconductor physics model compression via Data-driven Discrete Exterior Calculus

8th European Congress on Computational Methods in Applied Sciences and Engineering

Andy Huang, Nathaniel Albert Trask, Xujiao Gao, Shahed Reza, Ravi Ghanshyam Patel, Christopher Brissette, Xiaozhe Hu

Conference Presentation – 2022 Conference Presentation 2022

Error-in-variables modelling for operator learning

AIRES Workshop

Ravi Ghanshyam Patel, Indu Manickam, Mamikon Gulian, Myoungkyu Lee

Conference Presentation – 2022 Conference Presentation 2022

Error-in-variables modelling for operator learning

Msml22

Ravi Ghanshyam Patel, Indu Manickam, Mamikon Gulian, Myoungkyu Lee

Conference Paper – 2022 Conference Paper 2022

Error-in-variables modelling for operator learning

Mathematical and Scientific Machine Learning 2022 (MSML2022)

Mamikon Gulian, Ravi Ghanshyam Patel, Indu Manickam, Lee Myoungkyu

Conference Paper – 2022 Conference Paper 2022

Machine learning of Physics-Informed Graph Neural Networks from TCAD models

Mechanistic Machine Learning and Digital Twins for Computational Science, Engineering & Technology (IACM conference) 2021

Andy Huang, Nathaniel Albert Trask, Xujiao Gao, Shahed Reza, Ravi Ghanshyam Patel, Christopher Brissette, Xiaozhe Hu

Conference Presentation – 2021 Conference Presentation 2021

Machine learning surrogates of high-fidelity electrical models

REHEDS External Review

Andy Huang, Xujiao Gao, Shahed Reza, Nathaniel Albert Trask, Ian Zachary Wilcox, Candace Pauline Diaz, Ravi Ghanshyam Patel

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

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

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 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

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

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

Control volume PINNs: a method for solving inverse problems with hyperbolic PDEs

CRUNCH seminar

Ravi Ghanshyam Patel

https://www.osti.gov/search/identifier:1840510

Presentation (non-conference) – 2021 Presentation (non-conference) 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

PDE discovery with machine learning

University of New Mexico Applied Math Seminar

Ravi Ghanshyam Patel

Presentation (non-conference) – 2020 Presentation (non-conference) 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

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
Document Title Type Year
Results 1–25 of 32