| Reynolds averaged turbulence modelling using deep neural networks with embedded invariance J Ling, A Kurzawski, J Templeton Journal of Fluid Mechanics 807, 155-166, 2016 | 1164 | 2016 |
| Machine learning strategies for systems with invariance properties J Ling, R Jones, J Templeton Journal of Computational Physics 318, 22-35, 2016 | 345 | 2016 |
| Evaluation of machine learning algorithms for prediction of regions of high Reynolds averaged Navier Stokes uncertainty J Ling, J Templeton Physics of Fluids 27 (8), 085103, 2015 | 340 | 2015 |
| Model based design of a microfluidic mixer driven by induced charge electroosmosis CK Harnett, J Templeton, KA Dunphy-Guzman, YM Senousy, MP Kanouff Lab on a Chip 8 (4), 565-572, 2008 | 182 | 2008 |
| A toolbox of Hamilton-Jacobi solvers for analysis of nondeterministic continuous and hybrid systems IM Mitchell, JA Templeton Hybrid Systems: Computation and Control: 8th International Workshop, HSCC …, 2005 | 154 | 2005 |
| A material frame approach for evaluating continuum variables in atomistic simulations JA Zimmerman, RE Jones, JA Templeton Journal of Computational Physics 229 (6), 2364-2389, 2010 | 92 | 2010 |
| Comparison of molecular dynamics with classical density functional and poisson–boltzmann theories of the electric double layer in nanochannels JW Lee, RH Nilson, JA Templeton, SK Griffiths, A Kung, BM Wong Journal of chemical theory and computation 8 (6), 2012-2022, 2012 | 81 | 2012 |
| An atomistic-to-continuum coupling method for heat transfer in solids GJ Wagner, RE Jones, JA Templeton, ML Parks Computer Methods in Applied Mechanics and Engineering 197 (41-42), 3351-3365, 2008 | 80 | 2008 |
| Predicting the mechanical response of oligocrystals with deep learning AL Frankel, RE Jones, C Alleman, JA Templeton Computational Materials Science 169, 109099, 2019 | 72 | 2019 |
| An eddy-viscosity based near-wall treatment for coarse grid large-eddy simulation JA Templeton, G Medic, G Kalitzin Physics of fluids 17 (10), 105101, 2005 | 50 | 2005 |
| An efficient wall model for large-eddy simulation based on optimal control theory JA Templeton, M Wang, P Moin Physics of Fluids 18 (2), 025101, 2006 | 41 | 2006 |
| A predictive wall model for large-eddy simulation based on optimal control techniques JA Templeton, M Wang, P Moin Physics of Fluids 20 (6), 065104, 2008 | 37 | 2008 |
| Machine learning models of plastic flow based on representation theory RE Jones, JA Templeton, CM Sanders, JT Ostien arXiv preprint arXiv:1809.00267, 2018 | 29 | 2018 |
| Electron transport enhanced molecular dynamics for metals and semi‐metals RE Jones, JA Templeton, GJ Wagner, D Olmsted, NA Modine International Journal for Numerical Methods in Engineering 83 (8‐9), 940-967, 2010 | 29 | 2010 |
| Comparison of molecular and primitive solvent models for electrical double layers in nanochannels JW Lee, JA Templeton, KK Mandadapu, JA Zimmerman Journal of chemical theory and computation 9 (7), 3051-3061, 2013 | 22 | 2013 |
| Model reduction with MapReduce-enabled tall and skinny singular value decomposition PG Constantine, DF Gleich, Y Hou, J Templeton SIAM Journal on Scientific Computing 36 (5), S166-S191, 2014 | 19 | 2014 |
| A long-range electric field solver for molecular dynamics based on atomistic-to-continuum modeling JA Templeton, RE Jones, JW Lee, JA Zimmerman, BM Wong Journal of Chemical Theory and Computation 7 (6), 1736-1749, 2011 | 19 | 2011 |
| Uncertainty quantification in LES of channel flow C Safta, M Blaylock, J Templeton, S Domino, K Sargsyan, H Najm International Journal for Numerical Methods in Fluids 83 (4), 376-401, 2017 | 18 | 2017 |
| Application of a field-based method to spatially varying thermal transport problems in molecular dynamics JA Templeton, RE Jones, GJ Wagner Modelling and Simulation in Materials Science and Engineering 18 (8), 085007, 2010 | 17 | 2010 |
| Inference and uncertainty propagation of atomistically informed continuum constitutive laws, part 2: Generalized continuum models based on gaussian processes M Salloum, JA Templeton International Journal for Uncertainty Quantification 4 (2), 2014 | 15 | 2014 |
Reese E. JonesSandia National LaboratoriesVerified email at sandia.gov
