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Nicholas Lubbers
Nicholas Lubbers
Computer, Computational, and Statistical Sciences Division, Los Alamos National Laboratory
Bestätigte E-Mail-Adresse bei lanl.gov
Titel
Zitiert von
Zitiert von
Jahr
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
7052013
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), 2018
7032018
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), 2903, 2019
6432019
Machine learning predicts laboratory earthquakes
B Rouet‐Leduc, C Hulbert, N Lubbers, K Barros, CJ Humphreys, ...
Geophysical Research Letters 44 (18), 9276-9282, 2017
4362017
Hierarchical modeling of molecular energies using a deep neural network
N Lubbers, JS Smith, K Barros
The Journal of chemical physics 148 (24), 2018
3272018
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), 134, 2020
2112020
Inferring low-dimensional microstructure representations using convolutional neural networks
N Lubbers, T Lookman, K Barros
Physical Review E 96 (5), 052111, 2017
1442017
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
135*2020
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
1262018
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
1102018
Model independent direct detection analyses
AL Fitzpatrick, W Haxton, E Katz, N Lubbers, Y Xu
arXiv preprint arXiv:1211.2818, 2012
932012
Automated discovery of a robust interatomic potential for aluminum
JS Smith, B Nebgen, N Mathew, J Chen, N Lubbers, L Burakovsky, ...
Nature communications 12 (1), 1257, 2021
892021
Computationally efficient multiscale neural networks applied to fluid flow in complex 3D porous media
JE Santos, Y Yin, H Jo, W Pan, Q Kang, HS Viswanathan, M Prodanović, ...
Transport in porous media 140 (1), 241-272, 2021
842021
Extending machine learning beyond interatomic potentials for predicting molecular properties
N Fedik, R Zubatyuk, M Kulichenko, N Lubbers, JS Smith, B Nebgen, ...
Nature Reviews Chemistry 6 (9), 653-672, 2022
762022
The rise of neural networks for materials and chemical dynamics
M Kulichenko, JS Smith, B Nebgen, YW Li, N Fedik, AI Boldyrev, ...
The Journal of Physical Chemistry Letters 12 (26), 6227-6243, 2021
642021
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
542018
Uncertainty-driven dynamics for active learning of interatomic potentials
M Kulichenko, K Barros, N Lubbers, YW Li, R Messerly, S Tretiak, ...
Nature Computational Science 3 (3), 230-239, 2023
472023
Exploring the frontiers of condensed-phase chemistry with a general reactive machine learning potential
S Zhang, MZ Makoś, RB Jadrich, E Kraka, K Barros, BT Nebgen, S Tretiak, ...
Nature Chemistry 16 (5), 727-734, 2024
432024
Machine learned Hückel theory: Interfacing physics and deep neural networks
T Zubatiuk, B Nebgen, N Lubbers, JS Smith, R Zubatyuk, G Zhou, C Koh, ...
The Journal of Chemical Physics 154 (24), 2021
412021
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
412020
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