| Solving Lattice QCD systems of equations using mixed precision solvers on GPUs MA Clark, R Babich, K Barros, RC Brower, C Rebbi Computer Physics Communications 181 (9), 1517-1528, 2010 | 388 | 2010 |
| Approaching coupled cluster accuracy with a general-purpose neural network potential through transfer learning JS Smith, BT Nebgen, R Zubatyuk, N Lubbers, C Devereux, K Barros, ... Nature communications 10 (1), 1-8, 2019 | 153* | 2019 |
| Machine learning predicts laboratory earthquakes B Rouet‐Leduc, C Hulbert, N Lubbers, K Barros, CJ Humphreys, ... Geophysical Research Letters 44 (18), 9276-9282, 2017 | 145 | 2017 |
| Hierarchical modeling of molecular energies using a deep neural network N Lubbers, JS Smith, K Barros The Journal of chemical physics 148 (24), 241715, 2018 | 128 | 2018 |
| Dielectric effects in the self-assembly of binary colloidal aggregates K Barros, E Luijten Physical review letters 113 (1), 017801, 2014 | 84 | 2014 |
| Freezing into stripe states in two-dimensional ferromagnets and crossing probabilities in critical percolation K Barros, PL Krapivsky, S Redner Physical Review E 80 (4), 040101, 2009 | 69 | 2009 |
| Inferring low-dimensional microstructure representations using convolutional neural networks N Lubbers, T Lookman, K Barros Physical Review E 96 (5), 052111, 2017 | 67 | 2017 |
| Discovering a transferable charge assignment model using machine learning AE Sifain, N Lubbers, BT Nebgen, JS Smith, AY Lokhov, O Isayev, ... The journal of physical chemistry letters 9 (16), 4495-4501, 2018 | 56 | 2018 |
| Transferable dynamic molecular charge assignment using deep neural networks B Nebgen, N Lubbers, JS Smith, AE Sifain, A Lokhov, O Isayev, ... Journal of chemical theory and computation 14 (9), 4687-4698, 2018 | 53 | 2018 |
| Efficient Langevin simulation of coupled classical fields and fermions K Barros, Y Kato Physical Review B 88 (23), 235101, 2013 | 53 | 2013 |
| Efficient and accurate simulation of dynamic dielectric objects K Barros, D Sinkovits, E Luijten The Journal of chemical physics 140 (6), 064903, 2014 | 51 | 2014 |
| Learning molecular energies using localized graph kernels G Ferré, T Haut, K Barros The Journal of chemical physics 146 (11), 114107, 2017 | 45 | 2017 |
| Vortex crystals with chiral stripes in itinerant magnets R Ozawa, S Hayami, K Barros, GW Chern, Y Motome, CD Batista Journal of the Physical Society of Japan 85 (10), 103703, 2016 | 45 | 2016 |
| Exotic magnetic orderings in the kagome Kondo-lattice model K Barros, JWF Venderbos, GW Chern, CD Batista Physical Review B 90 (24), 245119, 2014 | 38 | 2014 |
| Direct observation of stringlike collective motion in a two-dimensional driven granular fluid CR Berardi, K Barros, JF Douglas, W Losert Physical Review E 81 (4), 041301, 2010 | 37 | 2010 |
| Optimisation of GaN LEDs and the reduction of efficiency droop using active machine learning B Rouet-Leduc, K Barros, T Lookman, CJ Humphreys Scientific reports 6, 24862, 2016 | 27 | 2016 |
| Comparison of efficient techniques for the simulation of dielectric objects in electrolytes Z Gan, H Wu, K Barros, Z Xu, E Luijten Journal of Computational Physics 291, 317-333, 2015 | 27 | 2015 |
| Blasting through lattice calculations using CUDA K Barros, R Babich, R Brower, MA Clark, C Rebbi arXiv preprint arXiv:0810.5365, 2008 | 27 | 2008 |
| Spatial adaptive sampling in multiscale simulation B Rouet-Leduc, K Barros, E Cieren, V Elango, C Junghans, T Lookman, ... Computer Physics Communications 185 (7), 1857-1864, 2014 | 24 | 2014 |
| Distributed database kriging for adaptive sampling (D2KAS) D Roehm, RS Pavel, K Barros, B Rouet-Leduc, AL McPherson, ... Computer Physics Communications 192, 138-147, 2015 | 22 | 2015 |
Nicholas LubbersStaff Scientist, Computer, Computational, and Statistical Sciences Division, LANL確認したメール アドレス: bu.edu
