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Nicholas Lubbers
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2020 – today
- 2024
- [i9]Emily Shinkle, Aleksandra Pachalieva, Riti Bahl, Sakib Matin, Brendan Gifford, Galen T. Craven, Nicholas Lubbers:
Thermodynamic Transferability in Coarse-Grained Force Fields using Graph Neural Networks. CoRR abs/2406.12112 (2024) - 2023
- [j8]Andrew Rohskopf
, C. Sievers, Nicholas Lubbers
, Mary Alice Cusentnio
, James Goff
, Jan Janssen
, Megan McCarthy
, David Montes Oca de Zapiain
, Svetoslav Nikolov
, Khachik Sargsyan
, Dionysios Sema
, Ember Sikorski
, Logan Williams
, Aidan P. Thompson
, Mitchell A. Wood
:
FitSNAP: Atomistic machine learning with LAMMPS. J. Open Source Softw. 8(83): 5118 (2023) - [j7]Javier E. Santos
, Zachary R. Fox, Arvind Mohan, Daniel O'Malley
, Hari S. Viswanathan, Nicholas Lubbers:
Development of the Senseiver for efficient field reconstruction from sparse observations. Nat. Mac. Intell. 5(11): 1317-1325 (2023) - [j6]Maksim Kulichenko, Kipton Barros
, Nicholas Lubbers, Ying Wai Li, Richard A. Messerly, Sergei Tretiak, Justin S. Smith, Benjamin T. Nebgen
:
Uncertainty-driven dynamics for active learning of interatomic potentials. Nat. Comput. Sci. 3(3): 230-239 (2023) - [j5]Anastasiia Kim
, Sanna Sevanto, Eric R. Moore, Nicholas Lubbers:
Latent Dirichlet Allocation modeling of environmental microbiomes. PLoS Comput. Biol. 19(6) (2023) - [c1]Javier E. Santos, Zachary R. Fox, Nicholas Lubbers, Yen Ting Lin:
Blackout Diffusion: Generative Diffusion Models in Discrete-State Spaces. ICML 2023: 9034-9059 - [i8]Javier E. Santos, Zachary R. Fox, Nicholas Lubbers, Yen Ting Lin:
Blackout Diffusion: Generative Diffusion Models in Discrete-State Spaces. CoRR abs/2305.11089 (2023) - 2022
- [j4]Aleksandra Pachalieva
, Robert S. Pavel
, Javier E. Santos
, Abdourahmane Diaw
, Nicholas Lubbers
, Mohammed Mehana
, Jeffrey R. Haack
, Hari S. Viswanathan
, Daniel Livescu
, Timothy C. Germann
, Christoph Junghans
:
GLUE Code: A framework handling communication and interfaces between scales. J. Open Source Softw. 7(80): 4822 (2022) - [i7]Satish Karra, Mohammed Mehana, Nicholas Lubbers, Yu Chen, Abdourahmane Diaw, Javier E. Santos, Aleksandra Pachalieva, Robert S. Pavel, Jeffrey R. Haack, Michael M. McKerns, Christoph Junghans
, Qinjun Kang
, Daniel Livescu, Timothy C. Germann, Hari S. Viswanathan:
Predictive Scale-Bridging Simulations through Active Learning. CoRR abs/2209.09811 (2022) - 2021
- [j3]Michael Tynes
, Wenhao Gao
, Daniel J. Burrill, Enrique R. Batista
, Danny Perez
, Ping Yang
, Nicholas Lubbers:
Pairwise Difference Regression: A Machine Learning Meta-algorithm for Improved Prediction and Uncertainty Quantification in Chemical Search. J. Chem. Inf. Model. 61(8): 3846-3857 (2021) - [j2]Kun Wang, Yu Chen, Mohammed Mehana
, Nicholas Lubbers, Kane C. Bennett, Qinjun Kang, Hari S. Viswanathan, Timothy C. Germann
:
A physics-informed and hierarchically regularized data-driven model for predicting fluid flow through porous media. J. Comput. Phys. 443: 110526 (2021) - [i6]Javier E. Santos, Ying Yin, Honggeun Jo, Wen Pan, Qinjun Kang, Hari S. Viswanathan, Masa Prodanovic, Michael J. Pyrcz, Nicholas Lubbers:
Multi-Scale Neural Networks for to Fluid Flow in 3D Porous Media. CoRR abs/2102.07625 (2021) - 2020
- [i5]Justin S. Smith, Benjamin T. Nebgen, Nithin Mathew, Jie Chen, Nicholas Lubbers, Leonid Burakovsky, Sergei Tretiak, Hai Ah Nam, Timothy C. Germann, Saryu Fensin, Kipton Barros:
Automated discovery of a robust interatomic potential for aluminum. CoRR abs/2003.04934 (2020) - [i4]Javier E. Santos, Mohammed Mehana, Hao Wu, Masa Prodanovic, Michael J. Pyrcz, Qinjun Kang, Nicholas Lubbers, Hari S. Viswanathan:
Modeling nanoconfinement effects using active learning. CoRR abs/2005.02587 (2020) - [i3]Rahulkumar Gayatri, Stan G. Moore, Evan Weinberg, Nicholas Lubbers, Sarah Anderson, Jack Deslippe, Danny Perez, Aidan P. Thompson:
Rapid Exploration of Optimization Strategies on Advanced Architectures using TestSNAP and LAMMPS. CoRR abs/2011.12875 (2020)
2010 – 2019
- 2018
- [i2]Justin S. Smith, Ben Nebgen, Nicholas Lubbers, Olexandr Isayev, Adrian E. Roitberg:
Less is more: sampling chemical space with active learning. CoRR abs/1801.09319 (2018) - 2016
- [i1]Nicholas Lubbers, Turab Lookman, Kipton Barros:
Inferring low-dimensional microstructure representations using convolutional neural networks. CoRR abs/1611.02764 (2016) - 2010
- [j1]Mark W. Coffey, Nicholas Lubbers:
On generalized harmonic number sums. Appl. Math. Comput. 217(2): 689-698 (2010)
Coauthor Index
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last updated on 2024-07-25 20:22 CEST by the dblp team
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