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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 2024-10-07 22:14 CEST by the dblp team
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