| Dakota, a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis: version 6.13 user's … BM Adams, WJ Bohnhoff, KR Dalbey, MS Ebeida, JP Eddy, MS Eldred, ... Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2020 | 1562 | 2020 |
| Dakota BM Adams, MS Ebeida, MS Eldred, JD Jakeman, LP Swiler, JA Stephens, ... A Multilevel Parallel Object-Oriented Framework for Design Optimization …, 2014 | 98 | 2014 |
| Accelerating finite-temperature Kohn-Sham density functional theory with deep neural networks JA Ellis, L Fiedler, GA Popoola, NA Modine, JA Stephens, AP Thompson, ... Physical Review B 104 (3), 035120, 2021 | 57 | 2021 |
| Pd ensemble effects on oxygen hydrogenation in AuPd alloys: A combined density functional theory and Monte Carlo study HC Ham, JA Stephens, GS Hwang, J Han, SW Nam, TH Lim Catalysis today 165 (1), 138-144, 2011 | 51 | 2011 |
| Role of small Pd ensembles in boosting CO oxidation in AuPd alloys HC Ham, JA Stephens, GS Hwang, J Han, SW Nam, TH Lim The Journal of Physical Chemistry Letters 3 (5), 566-570, 2012 | 46 | 2012 |
| Atomic arrangements of AuPt/Pt (111) and AuPd/Pd (111) surface alloys: A combined density functional theory and Monte Carlo study JA Stephens, HC Ham, GS Hwang The Journal of Physical Chemistry C 114 (49), 21516-21523, 2010 | 30 | 2010 |
| On the nature and origin of Si surface segregation in amorphous AuSi alloys SH Lee, JA Stephens, GS Hwang The Journal of Physical Chemistry C 114 (7), 3037-3041, 2010 | 21 | 2010 |
| Uncertainty quantification of fluidized beds using a data-driven framework VMK Kotteda, JA Stephens, W Spotz, V Kumar, A Kommu Powder technology 354, 709-718, 2019 | 12 | 2019 |
| Atomic arrangements in AuPt/Pt (100) and AuPd/Pd (100) surface alloys: A Monte Carlo study using first principles-based cluster expansions JA Stephens, GS Hwang The Journal of Physical Chemistry C 115 (43), 21205-21210, 2011 | 9 | 2011 |
| Multilevel Parallel Object-Oriented Framework for Design Optimization BM Adams, LE Bauman, W Bohnhoff, K Dalbey, M Ebeida, J Eddy, ... Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis …, 2015 | 8 | 2015 |
| Deployment of Multifidelity Uncertainty Quantification for Thermal Battery Assessment Part I: Algorithms and Single Cell Results BM Adams, MS Eldred, G Geraci, T Portone, EM Ridgway, JA Stephens, ... Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2022 | 4 | 2022 |
| Automated Algorithms for Quantum-Level Accuracy in Atomistic Simulations: LDRD Final Report. AP Thompson, PA Schultz, P Crozier, SG Moore, LP Swiler, JA Stephens, ... Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2014 | 3 | 2014 |
| Strain effects on ensemble populations in AuPd/Pd (100) surface alloys JA Stephens, GS Hwang The Journal of Chemical Physics 139 (16), 2013 | 3 | 2013 |
| Developing uncertainty quantification strategies in electromagnetic problems involving highly resonant cavities S Campione, JA Stephens, N Martin, A Eckert, LK Warne, G Huerta, ... Journal of Verification, Validation and Uncertainty Quantification 6 (4), 041003, 2021 | 1 | 2021 |
| Dakota Optimization and UQ: Explore and Predict with Confidence. BM Adams, JA Stephens Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2018 | 1 | 2018 |
| Dakota Software Training: Uncertainty Quantification. BM Adams, PD Hough, JA Stephens Sandia National Lab.(SNL-NM), Albuquerque, NM (United States); Sandia …, 2016 | 1 | 2016 |
| ILPAC Advanced Practical Chemistry Resource Pack Independent Learning Project for Advanced Chemistry Advanced Practical Chemistry Resource Pack A Lainchbury, J Stephens, A Thompson John Murray, 1997 | 1 | 1997 |
| Resolving Computational Challenges in Accelerating Electronic Structure Calculations using Machine Learning JS Fox, JA Stephens, N Modine, LP Swiler, S Rajamanickam NeurIPS 2022 AI for Science: Progress and Promises, 2022 | | 2022 |
| Accelerating Multiscale Materials Modeling with Machine Learning NA Modine, JA Stephens, LP Swiler, A Thompson, DJ Vogel, L Feilder, ... Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2022 | | 2022 |
| Overview of the latest features and capabilities in the Dakota software. J Stephens, D Seidl, B Adams, G Geraci Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2022 | | 2022 |
