Nicholas Lubbers

34 papers A* 2Journal 32

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Projected Hessian Learning: Fast Curvature Supervision for Accurate Machine-Learning Interatomic Potentials. CoRR Austin Rodriguez, Justin S. Smith, Sakib Matin, Nicholas Lubbers, Kipton Barros, Jose L. Mendoza-Cortes
2025	J	`jnl`	Discrete Spatial Diffusion: Intensity-Preserving Diffusion Modeling. CoRR Javier E. Santos, Agnese Marcato, Roman Colman, Nicholas Lubbers, Yen Ting Lin
2025	J	`jnl`	Ensemble Knowledge Distillation for Machine Learning Interatomic Potentials. CoRR Sakib Matin, Emily Shinkle, Yulia Pimonova, Galen T. Craven, Aleksandra Pachalieva, Ying Wai Li, Kipton Barros, Nicholas Lubbers
2025	J	`jnl`	Flexible Moment-Invariant Bases from Irreducible Tensors. CoRR Roxana Bujack, Emily Shinkle, Alice Allen, Tomás Suk, Nicholas Lubbers
2025	J	`jnl`	GPU-Accelerated Charge-Equilibration for Shadow Molecular Dynamics in Python. CoRR Mehmet Cagri Kaymak, Nicholas Lubbers, Christian F. A. Negre, Michael E. Wall, Anders M. N. Niklasson
2025	J	`jnl`	Including Physics-Informed Atomization Constraints in Neural Networks for Reactive Chemistry. J. Chem. Inf. Model. Shuhao Zhang, Michael Chigaev, Olexandr Isayev, Richard A. Messerly, Nicholas Lubbers
2025	J	`jnl`	Meta-Learning Linear Models for Molecular Property Prediction. CoRR Yulia Pimonova, Michael G. Taylor, Alice Allen, Ping Yang, Nicholas Lubbers
2025	A*	`conf`	Model-Agnostic Knowledge Guided Correction for Improved Neural Surrogate Rollout. ICLR Bharat Srikishan, Daniel O'Malley, Mohamed Mehana, Nicholas Lubbers, Nikhil Muralidhar
2025	J	`jnl`	Model-Agnostic Knowledge Guided Correction for Improved Neural Surrogate Rollout. CoRR Bharat Srikishan, Daniel O'Malley, Mohamed Mehana, Nicholas Lubbers, Nikhil Muralidhar
2025	J	`jnl`	Multi-fidelity learning for interatomic potentials: low-level forces and high-level energies are all you need Mach. Learn. Sci. Technol. Mitchell Messerly, Sakib Matin, Alice E. A. Allen, Benjamin T. Nebgen, Kipton Barros, Justin S. Smith, Nicholas Lubbers, Richard A. Messerly
2025	J	`jnl`	Optimal Invariant Bases for Atomistic Machine Learning. CoRR Alice E. A. Allen, Emily Shinkle, Roxana Bujack, Nicholas Lubbers
2025	J	`jnl`	Statistical Insight into Meta-Learning via Predictor Subspace Characterization and Quantification of Task Diversity. CoRR Saptati Datta, Nicolas W. Hengartner, Yulia Pimonova, Natalie E. Klein, Nicholas Lubbers
2025	J	`jnl`	Toward machine learning interatomic potentials for modeling uranium mononitride. Mach. Learn. Sci. Technol. Lorena Alzate-Vargas, Kashi N. Subedi, Nicholas Lubbers, Michael W. D. Cooper, Roxanne M. Tutchton, Tammie Gibson, Richard A. Messerly
2024	J	`jnl`	Journey over destination: dynamic sensor placement enhances generalization. Mach. Learn. Sci. Technol. Agnese Marcato, Eric Guiltinan, Hari S. Viswanathan, Daniel O'Malley, Nicholas Lubbers, Javier E. Santos
2024	J	`jnl`	Learning a general model of single phase flow in complex 3D porous media. Mach. Learn. Sci. Technol. Javier E. Santos, Agnese Marcato, Qinjun Kang, Mohamed Mehana, Daniel O'Malley, Hari S. Viswanathan, Nicholas Lubbers
2024	J	`jnl`	Thermodynamic Transferability in Coarse-Grained Force Fields using Graph Neural Networks. CoRR Emily Shinkle, Aleksandra Pachalieva, Riti Bahl, Sakib Matin, Brendan Gifford, Galen T. Craven, Nicholas Lubbers
2023	A*	`conf`	Blackout Diffusion: Generative Diffusion Models in Discrete-State Spaces. ICML Javier E. Santos, Zachary R. Fox, Nicholas Lubbers, Yen Ting Lin
2023	J	`jnl`	Blackout Diffusion: Generative Diffusion Models in Discrete-State Spaces. CoRR Javier E. Santos, Zachary R. Fox, Nicholas Lubbers, Yen Ting Lin
2023	J	`jnl`	Development of the Senseiver for efficient field reconstruction from sparse observations. Nat. Mac. Intell. Javier E. Santos, Zachary R. Fox, Arvind T. Mohan, Daniel O'Malley, Hari S. Viswanathan, Nicholas Lubbers
2023	J	`jnl`	FitSNAP: Atomistic machine learning with LAMMPS. J. Open Source Softw. Andrew Rohskopf, C. Sievers, Nicholas Lubbers, Mary Alice Cusentnio, James Goff, Jan Janssen, Megan J. McCarthy, David Montes Oca de Zapiain, Svetoslav Nikolov, Khachik Sargsyan, Dionysios Sema, Ember Sikorski, Logan Williams, Aidan P. Thompson, Mitchell A. Wood
2023	J	`jnl`	Improved quality metrics for association and reproducibility in chromatin accessibility data using mutual information. BMC Bioinform. Cullen Roth, Vrinda Venu, Vanessa Job, Nicholas Lubbers, Karissa Y. Sanbonmatsu, Christina R. Steadman, Shawn R. Starkenburg
2023	J	`jnl`	Latent Dirichlet Allocation modeling of environmental microbiomes. PLoS Comput. Biol. Anastasiia Kim, Sanna Sevanto, Eric R. Moore, Nicholas Lubbers
2023	J	`jnl`	Uncertainty-driven dynamics for active learning of interatomic potentials. Nat. Comput. Sci. Maksim Kulichenko, Kipton Barros, Nicholas Lubbers, Ying Wai Li, Richard A. Messerly, Sergei Tretiak, Justin S. Smith, Benjamin T. Nebgen
2022	J	`jnl`	GLUE Code: A framework handling communication and interfaces between scales. J. Open Source Softw. 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
2022	J	`jnl`	Predictive Scale-Bridging Simulations through Active Learning. CoRR 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
2021	J	`jnl`	A physics-informed and hierarchically regularized data-driven model for predicting fluid flow through porous media. J. Comput. Phys. Kun Wang, Yu Chen, Mohammed Mehana, Nicholas Lubbers, Kane C. Bennett, Qinjun Kang, Hari S. Viswanathan, Timothy C. Germann
2021	J	`jnl`	Multi-Scale Neural Networks for to Fluid Flow in 3D Porous Media. CoRR Javier E. Santos, Ying Yin, Honggeun Jo, Wen Pan, Qinjun Kang, Hari S. Viswanathan, Masa Prodanovic, Michael J. Pyrcz, Nicholas Lubbers
2021	J	`jnl`	Pairwise Difference Regression: A Machine Learning Meta-algorithm for Improved Prediction and Uncertainty Quantification in Chemical Search. J. Chem. Inf. Model. Michael Tynes, Wenhao Gao, Daniel J. Burrill, Enrique R. Batista, Danny Perez, Ping Yang, Nicholas Lubbers
2020	J	`jnl`	Automated discovery of a robust interatomic potential for aluminum. CoRR 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
2020	J	`jnl`	Modeling nanoconfinement effects using active learning. CoRR Javier E. Santos, Mohammed Mehana, Hao Wu, Masa Prodanovic, Michael J. Pyrcz, Qinjun Kang, Nicholas Lubbers, Hari S. Viswanathan
2020	J	`jnl`	Rapid Exploration of Optimization Strategies on Advanced Architectures using TestSNAP and LAMMPS. CoRR Rahulkumar Gayatri, Stan G. Moore, Evan Weinberg, Nicholas Lubbers, Sarah Anderson, Jack Deslippe, Danny Perez, Aidan P. Thompson
2018	J	`jnl`	Less is more: sampling chemical space with active learning. CoRR Justin S. Smith, Ben Nebgen, Nicholas Lubbers, Olexandr Isayev, Adrian E. Roitberg
2016	J	`jnl`	Inferring low-dimensional microstructure representations using convolutional neural networks. CoRR Nicholas Lubbers, Turab Lookman, Kipton Barros
2010	J	`jnl`	On generalized harmonic number sums. Appl. Math. Comput. Mark W. Coffey, Nicholas Lubbers