Publications

Results 1–25 of 27
Date Inputs. Currently set to enter a start and end date.
Current Filters Clear all
Publication Type Year

Facilitating Atmospheric Source Inversion via Operator Regression

SIAM Conference on Mathematics of Planet Earth

Joseph Lee Hart, Mamikon Gulian, Indu Manickam, Laura Painton Swiler

Conference Presentation – 2022 Conference Presentation 2022

Facilitating Atmospheric Source Inversion via Deep Operator Network Surrogates

Esco 2022

Mamikon Gulian, Joseph Lee Hart, Indu Manickam, Laura Painton Swiler

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

Gaussian Process Regression constrained by Boundary Value Problems

Computer Methods in Applied Mechanics and Engineering

Mamikon Gulian, Ari Louis Frankel, Laura Painton Swiler

https://www.osti.gov/search/identifier:1831157

Journal Article – 2021 Journal Article 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

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

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

Constrained Gaussian Processes: A Survey

SIAM Computational Science and Engineering Conference 2021

Laura Painton Swiler, Mamikon Gulian, Ari Louis Frankel, Cosmin Safta, John Davis Jakeman

https://www.osti.gov/search/identifier:1847480

Conference Presentation – 2021 Conference Presentation 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

A Survey of Constrained Gaussian Process Regression: Approaches and Implementation Challenges

Journal of Machine Learning for Modeling and Computing

Laura Painton Swiler, Mamikon Gulian, Ari Louis Frankel, Cosmin Safta, John Davis Jakeman

https://www.osti.gov/search/identifier:1691455

Journal Article – 2020 Journal Article 2020

LDRD Project Summary: Incorporating physical constraints into Gaussian process surrogate models

Laura Painton Swiler, Mamikon Gulian, Ari Louis Frankel, John Davis Jakeman, Cosmin Safta

https://www.osti.gov/search/identifier:1668928

SAND Report – 2020 SAND Report 2020

Constrained Gaussian Processes: A Survey

SIAM Computational Science and Engineering 2021

Laura Painton Swiler, Mamikon Gulian, Ari Louis Frankel, Cosmin Safta, John Davis Jakeman

Abstract – 2020 Abstract 2020

A Survey of Constrained Gaussian Process Regression: Approaches and Implementation Challenges

PhILMs Webinar

Mamikon Gulian, Laura Painton Swiler, Ari Louis Frankel, Cosmin Safta, John Davis Jakeman

https://www.osti.gov/search/identifier:1814448

Conference Paper – 2020 Conference Paper 2020

A Survey of Constrained Gaussian Process Regression: Approaches and Implementation Challenges

Sandia Machine Learning and Deep Learning Workshop Skip to end of banner

Mamikon Gulian, Laura Painton Swiler, Ari Louis Frankel, John Davis Jakeman, Cosmin Safta

https://www.osti.gov/search/identifier:1812282

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

A Survey of Constrained Gaussian Process Regression: Approaches and Implementation Challenges

Machine Learning and Deep Learning Conference (Sandia Audience)

Mamikon Gulian, Laura Painton Swiler, Ari Louis Frankel, Cosmin Safta, John Davis Jakeman

Abstract – 2020 Abstract 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 Survey of Constrained Gaussian Process: Approaches and Implementation Challenges

Journal of Machine Learning for Modeling and Computing

Laura Painton Swiler, Mamikon Gulian, Ari Louis Frankel, Cosmin Safta, John Davis Jakeman

https://www.osti.gov/search/identifier:1725870

Journal Article – 2020 Journal Article 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

Data-driven learning of robust nonlocal physics from high-fidelity synthetic data

Arxiv

Huaiqian You, Yue Yu, Nathaniel Albert Trask, Mamikon Gulian, Marta D'Elia

https://www.osti.gov/search/identifier:1765754

Journal Article – 2020 Journal Article 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

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

Mathematical and Scientific Machine Learning Conference

Eric Christopher Cyr, Mamikon Gulian, Ravi Ghanshyam Patel, Mauro Perego, Nathaniel Albert Trask

https://www.osti.gov/search/identifier:1643463

Conference Paper – 2019 Conference Paper 2019

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, Stefanie (LLNL) Guenther, Lars (Emory University) Ruthotto, Jacob B Schroder, (UNM), Nico R. (TU Kaiserslautern) Gauger

Abstract – 2019 Abstract 2019
Document Title Type Year
Results 1–25 of 27