Publications
Publication | Type | Year |
---|---|---|
Solving stochastic inverse problems for property-structure linkages using data-consistent inversion and machine learningJom |
Journal Article – 2020 Journal Article | 2020 |
Solving stochastic inverse problems for structure-property linkages using data-consistent inversionTMS 2021 Annual Meeting & Exhibition |
Conference Paper – 2020 Conference Paper | 2020 |
Solving inverse problems for process-structure linkages using asynchronous parallel Bayesian optimizationTMS 2021 Annual Meeting & Exhibition |
Conference Paper – 2020 Conference Paper | 2020 |
Reification of latent microstructures: On supervised, unsupervised, and semi-supervised deep learning applications for microstructures in materials informatics |
SAND Report – 2020 SAND Report | 2020 |
Multi-fidelity machine-learning with uncertainty quantification and Bayesian optimization for materials design: Application to ternary random alloysThe Journal of Chemical Physics
|
Journal Article – 2020 Journal Article | 2020 |
On supervised and unsupervised deep learning applications for materials informaticsSandia Machine Learning and Deep Learning Workshop |
Conference Paper – 2020 Conference Paper | 2020 |
Multi-fidelity machine-learning with uncertainty quantification and Bayesian optimization for materials design: Application to ternary random alloysSandia MLDL Workshop
|
Abstract – 2020 Abstract | 2020 |
Multi-fidelity machine-learning with uncertainty quantification for materials design: Application to ternary random alloysarXiv |
Journal Article – 2020 Journal Article | 2020 |
Optimal Experimental Design for Prediction Based on Push-forward Probability MeasuresJournal of Computational Physics |
Journal Article – 2020 Journal Article | 2020 |
Impact of a minority relativistic electron tail interacting with a thermal plasma containing high-atomic-number impuritiesPhysics Review Letters
|
Journal Article – 2020 Journal Article | 2020 |
An active learning high-throughput microstructure calibration framework for solving inverse structure-process problems in materials informaticsActa Materialia |
Journal Article – 2020 Journal Article | 2020 |
Multiscale stochastic reduced-order model for uncertainty propagation using Fokker-Planck equation with microstructure evolution applicationsarXiv preprint |
Journal Article – 2020 Journal Article | 2020 |
aphBO-2GP-3B: A budgeted asynchronously-parallel multi-acquisition for known/unknown constrained Bayesian optimization on high-performing computing architecturearXiv |
Journal Article – 2020 Journal Article | 2020 |
Data-consistent Inversion For Stochastic Input-to-output MapsInverse Problems |
Journal Article – 2020 Journal Article | 2020 |
sMF-BO-2CoGP: A sequential multi-fidelity constrained Bayesian optimization framework for design applicationsASME Journal of Computing and Information Science in Engineering |
Journal Article – 2020 Journal Article | 2020 |
Convergence of Probability Densities using Approximate Models for Forward and Inverse Problems in Uncertainty Quantification: Extensions to LpSIAM/ASA Journal on Uncertainty Quantification |
Journal Article – 2020 Journal Article | 2020 |
Materials informatics: data-driven, materials design, and uncertainty quantification perspectivesSNL 13th annual postdoc technical showcase |
Conference Paper – 2019 Conference Paper | 2019 |
Moving Beyond Forward Simulation to Enable Data-informed Physics-based PredictionsColloquium at University of Colorado - Denver |
Presentation (non-conference) – 2019 Presentation (non-conference) | 2019 |
Convergence of Probability Densities using Approximate Models for Forward and Inverse Problems in Uncertainty QuantificationAMS Fall Southeastern Sectional Meeting |
Conference Paper – 2019 Conference Paper | 2019 |
sBF-BO-2CoGP: A sequential bi-fidelity constrained Bayesian optimization for design applicationsInternational Design Engineering Technical Conferences & Computers and Information in Engineering Conference |
Conference Paper – 2019 Conference Paper | 2019 |
A sequential bi-fidelity constrained Bayesian optimization for design applicationsASME International Design Engineering Technical Conferences & Computers and Information in Engineering Conference |
Conference Paper – 2019 Conference Paper | 2019 |
Solving Stochastic Inverse Problems using Approximate Push-forward Densities based on a Multi-fidelity Monte Carlo Method9th International Congress on Industrial and Applied Mathematics |
Conference Paper – 2019 Conference Paper | 2019 |
Using High Performance Computing to Enable Data-informed Multiscale Modeling with Applications to Additive MaterialsEngineering Mechanics Institute Conference |
Conference Paper – 2019 Conference Paper | 2019 |
A step towards a versatile Bayesian optimization: constrained, asynchronous batch-parallel, multi-fidelity, and mixed-integer extensionsMUMS Transition Workshop and SPUQ |
Conference Paper – 2019 Conference Paper | 2019 |
Simultaneous Inversion of Shear Modulus and Traction Boundary Conditions in Biomechanical ImagingInverse Problems in Science and Engineering |
Journal Article – 2019 Journal Article | 2019 |
Document Title | Type | Year |