Nicholas Lubbers
Nicholas Lubbers
Staff Scientist, Computer, Computational, and Statistical Sciences Division, LANL
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The effective field theory of dark matter direct detection
AL Fitzpatrick, W Haxton, E Katz, N Lubbers, Y Xu
Journal of Cosmology and Astroparticle Physics 2013 (02), 004, 2013
Less is more: Sampling chemical space with active learning
JS Smith, B Nebgen, N Lubbers, O Isayev, AE Roitberg
The Journal of Chemical Physics 148 (24), 241733, 2018
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
Machine learning predicts laboratory earthquakes
B Rouet‐Leduc, C Hulbert, N Lubbers, K Barros, CJ Humphreys, ...
Geophysical Research Letters 44 (18), 9276-9282, 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
Inferring low-dimensional microstructure representations using convolutional neural networks
N Lubbers, T Lookman, K Barros
Physical Review E 96 (5), 052111, 2017
Model independent direct detection analyses
AL Fitzpatrick, W Haxton, E Katz, N Lubbers, Y Xu
arXiv preprint arXiv:1211.2818, 2012
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
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
Embedding Hard Physical Constraints in Neural Network Coarse-Graining of 3D Turbulence
AT Mohan, N Lubbers, D Livescu, M Chertkov
arXiv preprint arXiv:2002.00021, 2020
The ANI-1ccx and ANI-1x data sets, coupled-cluster and density functional theory properties for molecules
JS Smith, R Zubatyuk, B Nebgen, N Lubbers, K Barros, AE Roitberg, ...
Scientific Data 7 (1), 1-10, 2020
Earthquake Catalog‐Based Machine Learning Identification of Laboratory Fault States and the Effects of Magnitude of Completeness
N Lubbers, DC Bolton, J Mohd‐Yusof, C Marone, K Barros, PA Johnson
Geophysical Research Letters 45 (24), 13,269-13,276, 2018
On generalized harmonic number sums
MW Coffey, N Lubbers
Applied Mathematics and Computation 217 (2), 689-698, 2010
Machine learning for molecular dynamics with strongly correlated electrons
H Suwa, JS Smith, N Lubbers, CD Batista, GW Chern, K Barros
Physical Review B 99 (16), 161107, 2019
Modeling nanoconfinement effects using active learning
JE Santos, M Mehana, H Wu, M Prodanovic, Q Kang, N Lubbers, ...
The Journal of Physical Chemistry C 124 (40), 22200-22211, 2020
The Effect of Growth On Equality in Models of the Economy
K Liu, N Lubbers, W Klein, J Tobochnik, B Boghosian, H Gould
arXiv preprint arXiv:1305.0794, 2013
Machine Learned H\" uckel Theory: Interfacing Physics and Deep Neural Networks
T Zubatyuk, B Nebgen, N Lubbers, JS Smith, R Zubatyuk, G Zhou, C Koh, ...
arXiv preprint arXiv:1909.12963, 2019
Machine learning approaches for structural and thermodynamic properties of a Lennard-Jones fluid
GT Craven, N Lubbers, K Barros, S Tretiak
The Journal of Chemical Physics 153 (10), 104502, 2020
Graphics Processing Unit-Accelerated Semiempirical Born Oppenheimer Molecular Dynamics Using PyTorch
G Zhou, B Nebgen, N Lubbers, W Malone, AMN Niklasson, S Tretiak
Journal of Chemical Theory and Computation 16 (8), 4951-4962, 2020
Ex Machina Determination of Structural Correlation Functions
GT Craven, N Lubbers, K Barros, S Tretiak
The journal of physical chemistry letters 11 (11), 4372-4378, 2020
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Artículos 1–20