Nicholas Lubbers

Scientist, Computing and Artificial Intelligence Division, Los Alamos National Laboratory

Joined

January 2023

Names

Nicholas Lubbers (Preferred)

Emails

****@lanl.gov (Confirmed)

Personal Links

Google Scholar

ORCID

Career & Education History

Scientist

Computing and Artificial Intelligence Division, Los Alamos National Laboratory (lanl.gov)

2018 – Present

Advisors, Relations & Conflicts

No relations added

Expertise

No areas of expertise listed

Publications

Projected Hessian Learning: Fast Curvature Supervision for Accurate Machine-Learning Interatomic Potentials
Austin Rodriguez, Justin S. Smith, Sakib Matin, Nicholas Lubbers, Kipton Barros, Jose L. Mendoza-Cortes
- CoRR 2026
- Readers: Everyone
Meta-Learning Linear Models for Molecular Property Prediction
Yulia Pimonova, Michael G. Taylor, Alice Allen, Ping Yang, Nicholas Lubbers
- CoRR 2025
- Readers: Everyone
Statistical Insight into Meta-Learning via Predictor Subspace Characterization and Quantification of Task Diversity
Saptati Datta, Nicolas W. Hengartner, Yulia Pimonova, Natalie E. Klein, Nicholas Lubbers
- CoRR 2025
- Readers: Everyone
Discrete Spatial Diffusion: Intensity-Preserving Diffusion Modeling
Javier E. Santos, Agnese Marcato, Roman Colman, Nicholas Lubbers, Yen Ting Lin
- NeurIPS 2025 spotlight
- Readers: Everyone
Discrete Spatial Diffusion: Intensity-Preserving Diffusion Modeling
Javier E. Santos, Agnese Marcato, Roman Colman, Nicholas Lubbers, Yen Ting Lin
- CoRR 2025
- Readers: Everyone
Model-Agnostic Knowledge Guided Correction for Improved Neural Surrogate Rollout
Bharat Srikishan, Daniel O'Malley, Mohamed Mehana, Nicholas Lubbers, Nikhil Muralidhar
- CoRR 2025
- Readers: Everyone
Flexible Moment-Invariant Bases from Irreducible Tensors
Roxana Bujack, Emily Shinkle, Alice Allen, Tomás Suk, Nicholas Lubbers
- CoRR 2025
- Readers: Everyone
GPU-Accelerated Charge-Equilibration for Shadow Molecular Dynamics in Python
Mehmet Cagri Kaymak, Nicholas Lubbers, Christian F. A. Negre, Michael E. Wall, Anders M. N. Niklasson
- CoRR 2025
- Readers: Everyone
Optimal Invariant Bases for Atomistic Machine Learning
Alice E. A. Allen, Emily Shinkle, Roxana Bujack, Nicholas Lubbers
- CoRR 2025
- Readers: Everyone
Ensemble Knowledge Distillation for Machine Learning Interatomic Potentials
Sakib Matin, Emily Shinkle, Yulia Pimonova, Galen T. Craven, Aleksandra Pachalieva, Ying Wai Li, Kipton Barros, Nicholas Lubbers
- CoRR 2025
- Readers: Everyone

View all 38 publications

Co-Authors

Abdourahmane Diaw
Adrian E. Roitberg
Agnese Marcato
Aidan P. Thompson
Aleksandra Pachalieva
Alice Allen
Alice E. A. Allen
Anastasiia Kim
Anders M. N. Niklasson
Andrew Rohskopf
Arvind T. Mohan
Austin Rodriguez
Ben Nebgen
Benjamin T. Nebgen
Bharat Srikishan
Brendan Gifford
C. Sievers
Christian F. A. Negre
Christina R. Steadman
Christoph Junghans
Cullen Roth
Daniel J. Burrill
Daniel Livescu
Daniel O'Malley
Danny Perez

View all 112 co-authors