Publications

Advanced Search

Results 1–25 of 26

Scope

Center for Computing Research

All Sandia Publications

Publication Type

Author

Funding Source

Current Filters Clear all

Remove author filter×

Publication	Type	Year
Randomized Functional Sparse Tucker Tensor for Compression and Fast Visualization of Scientific Data 26th Ieee International Conference On High Performance Computing, Data, And Analytics Prashant Rai, Cannada Lewis, Alex Arkady Gorodetsky	Conference Paper – 2022 Conference Paper	2022
The Dakota Project: Connecting the Pipeline from Uncertainty Quantification R&D to Mission Impact NASA Langley HPC Seminar Series Michael S. Eldred, Gianluca Geraci, Alex Arkady Gorodetsky, John Davis Jakeman, Teresa Portone, Timothy Michael Wildey, Ahmad Rushdi, Daniel Thomas Seidl	Presentation (non-conference) – 2021 Presentation (non-conference)	2021
Advanced multilevel and multifidelity UQ strategies: applications, generalized model hierarchies, and data-driven approaches SIAM Conference of Uncertainty Quantification (UQ22) Teresa Portone, John Davis Jakeman, Alex Arkady Gorodetsky	Abstract – 2021 Abstract	2021
MFNets: data efficient all-at-once learning of multifidelity surrogates as directed networks of information sources Computational Mechanics Alex Arkady Gorodetsky, John Davis Jakeman, Gianluca Geraci https://www.osti.gov/search/identifier:1820427	Journal Article – 2021 Journal Article	2021
Efficient Deployment of Multifidelity Sampling Methods in Production Settings Usnccm16 Michael S. Eldred, Gianluca Geraci, Alex Arkady Gorodetsky, John Davis Jakeman, Teresa Portone	Conference Presentation – 2021 Conference Presentation	2021
Low-Rank Tensor Network Approximations for Earth System Model Siam Cse 2021 Cosmin Safta, Khachik Sargsyan, John Davis Jakeman, Alex Arkady Gorodetsky https://www.osti.gov/search/identifier:1854317	Conference Presentation – 2021 Conference Presentation	2021
Recent Advances in Adaptive Refinement of (Regression-Based) Multifidelity Surrogates for UQ Siam Cse21 Michael S. Eldred, Alex Arkady Gorodetsky, Gianluca Geraci, John Davis Jakeman, Teresa Portone https://www.osti.gov/search/identifier:1847573	Conference Presentation – 2021 Conference Presentation	2021
Low-rank Approximations for High-dimensional and Computationally Expensive Models World Congress on Computational Mechanics Cosmin Safta, John Davis Jakeman, Khachik Sargsyan, Alex Arkady Gorodetsky	Abstract – 2020 Abstract	2020
Multilevel / Multifidelity Sampling and Emulation for Forward UQ Applied Math Visioning Workshop Michael S. Eldred, Gianluca Geraci, Alex Arkady Gorodetsky, John Davis Jakeman https://www.osti.gov/search/identifier:1645988	Presentation (non-conference) – 2019 Presentation (non-conference)	2019
Uncertainty Quantification for E3SM Land Component using Low-Rank Surrogate Models American Geophysical Society Fall Meeting 2019 Cosmin Safta, Khachik Sargsyan, John Davis Jakeman, Alex Arkady Gorodetsky	Abstract – 2019 Abstract	2019
Recent Advancements for Multifidelity UQ and OUU in Dakota: Capability Overview and Perspectives US National Congress of Computational Mechanics Gianluca Geraci, Michael S. Eldred, Alex Arkady Gorodetsky, John Davis Jakeman https://www.osti.gov/search/identifier:1641419	Conference Paper – 2019 Conference Paper	2019
Experience with Multilevel/Multifidelity/Multi-Index Sampling and Surrogate Approaches for Forward Uncertainty Quantification 15th US National Congress on Computational Mechanics (USNCCM) Michael S. Eldred, Gianluca Geraci, Alex Arkady Gorodetsky, John Davis Jakeman https://www.osti.gov/search/identifier:1641388	Conference Paper – 2019 Conference Paper	2019
Exploiting Model Structure for Forward Propagation of Uncertainty in Earth System Models 3rd International Conference on Uncertainty Quantification in Computational Sciences and Engineering Cosmin Safta, Khachik Sargsyan, John Davis Jakeman, Alex Arkady Gorodetsky, Daniel Ricciuto https://www.osti.gov/search/identifier:1640926	Conference Paper – 2019 Conference Paper	2019
Low-Rank Functional Tensor Train Representations for High-Dimensional Computational Models FASTMath-4 Institute - All-Hands Meeting Cosmin Safta, John Davis Jakeman, Alex Arkady Gorodetsky https://www.osti.gov/search/identifier:1645344	Presentation (non-conference) – 2019 Presentation (non-conference)	2019
Gradient-based Optimization for Regression in the Functional Tensor-Train Format Alex Arkady Gorodetsky, John Davis Jakeman https://www.osti.gov/search/identifier:1733296	Report – 2018 Report	2018
Low-rank Tensor Integration for Gaussian Filtering of Continuous TIme Nonlinear Systems 56th IEEE Conference on Decision and Control Alex Arkady Gorodetsky, Sertac Karaman, Youssef Marzouk https://www.osti.gov/search/identifier:1486890	Conference Paper – 2017 Conference Paper	2017
Low-rank functional representations for analysis of high-dimensional models DOE ASCR Applied Mathematics Principal Investigator's (PI) Meeting Alex Arkady Gorodetsky	Display or Poster (non-conference) – 2017 Display or Poster (non-conference)	2017
Tractable Uncertainty Quantification: Exploiting Structure Sandia CIS Review John Davis Jakeman, Alex Arkady Gorodetsky, Michael S. Eldred https://www.osti.gov/search/identifier:1466103	Conference Paper – 2017 Conference Paper	2017
Low-rank functional decompositions with applications to stochastic optimal control 2017 Meeting of the International Linear Algebra Society Alex Arkady Gorodetsky https://www.osti.gov/search/identifier:1463960	Conference Paper – 2017 Conference Paper	2017
Multilevel-Multifidelity Expansions with Application to Forward UQ, OUU, and Emulator-Based Bayesian Inference 14th U.S. National Congress on Computational Mechanics (USNCCM14) Michael S. Eldred, Gianluca Geraci, Alex Arkady Gorodetsky, John Davis Jakeman https://www.osti.gov/search/identifier:1507501	Conference Paper – 2017 Conference Paper	2017
Sampling, Polynomial Chaos and Functional Tensor Train Multilevel/Multifidelity Strategies for Forward UQ SIAM Annual 17 Gianluca Geraci, Alex Arkady Gorodetsky, John Davis Jakeman, Michael S. Eldred https://www.osti.gov/search/identifier:1507076	Conference Paper – 2017 Conference Paper	2017
Compression for Stochastic Optimal Control Seminar at Los Alamos National Laboratory Alex Arkady Gorodetsky	Presentation (non-conference) – 2017 Presentation (non-conference)	2017
Optimization under uncertainty and high dimensional regression for additive manufacturing SIAM Conference on Optimization Bart G van Bloemen Waanders, Alex Arkady Gorodetsky https://www.osti.gov/search/identifier:1367311	Conference Paper – 2017 Conference Paper	2017
Low-rank functional approximation for Gaussian filtering Uncertainty Quantification and Data-Driven Modeling Alex Arkady Gorodetsky, Sertac Karaman, Youssef Marzouk https://www.osti.gov/search/identifier:1456416	Conference Paper – 2017 Conference Paper	2017
High-dimensional regression of low-rank functions Siam Cse Alex Arkady Gorodetsky, John Davis Jakeman https://www.osti.gov/search/identifier:1426383	Conference Paper – 2017 Conference Paper	2017
Document Title	Type	Year

Results 1–25 of 26

Publications

Randomized Functional Sparse Tucker Tensor for Compression and Fast Visualization of Scientific Data

The Dakota Project: Connecting the Pipeline from Uncertainty Quantification R&D to Mission Impact

Advanced multilevel and multifidelity UQ strategies: applications, generalized model hierarchies, and data-driven approaches

MFNets: data efficient all-at-once learning of multifidelity surrogates as directed networks of information sources

Efficient Deployment of Multifidelity Sampling Methods in Production Settings

Low-Rank Tensor Network Approximations for Earth System Model

Recent Advances in Adaptive Refinement of (Regression-Based) Multifidelity Surrogates for UQ

Low-rank Approximations for High-dimensional and Computationally Expensive Models

Multilevel / Multifidelity Sampling and Emulation for Forward UQ

Uncertainty Quantification for E3SM Land Component using Low-Rank Surrogate Models

Recent Advancements for Multifidelity UQ and OUU in Dakota: Capability Overview and Perspectives

Experience with Multilevel/Multifidelity/Multi-Index Sampling and Surrogate Approaches for Forward Uncertainty Quantification

Exploiting Model Structure for Forward Propagation of Uncertainty in Earth System Models

Low-Rank Functional Tensor Train Representations for High-Dimensional Computational Models

Gradient-based Optimization for Regression in the Functional Tensor-Train Format

Low-rank Tensor Integration for Gaussian Filtering of Continuous TIme Nonlinear Systems

Low-rank functional representations for analysis of high-dimensional models

Tractable Uncertainty Quantification: Exploiting Structure

Low-rank functional decompositions with applications to stochastic optimal control

Multilevel-Multifidelity Expansions with Application to Forward UQ, OUU, and Emulator-Based Bayesian Inference

Sampling, Polynomial Chaos and Functional Tensor Train Multilevel/Multifidelity Strategies for Forward UQ

Compression for Stochastic Optimal Control

Optimization under uncertainty and high dimensional regression for additive manufacturing

Low-rank functional approximation for Gaussian filtering

High-dimensional regression of low-rank functions