logo
科言猫学术研究的AI总结
language
手机端手机端
  • Phone Feature微信小程序
简体中文简体中文
notice消息通知
博客博客
delete
arrow
返回
N

Nicholas Lubbers

los alamos national laboratory

33H指数
157论文数
4.8K被引数
收录论文 45
发表时间
logo
Enhancing Molecular Dipole Moment Prediction with Multitask Machine Learning利用多任务机器学习提升分子偶极矩预测
errThe Journal of Physical Chemistry Letters
IF0
err2026-05-27
err0
PREAI
errWilliam Colglazier; Nicholas Lubbers; Sergei Tretiak; Anders M. N. Niklasson; Maksim Kulichenko
err分享
err收藏
Meta-learning linear models for molecular property prediction元学习线性模型用于分子性质预测
errDigital Discovery
IF5.6
err2026-05-14
err0
errOAAI
errYulia Pimonova; Michael G. Taylor; Alice Allen; Ping Yang; Nicholas Lubbers
err分享
err收藏
Science-guided transfer learning for molecular dynamics of confined fluids in shale nanopores科学指导的迁移学习在页岩纳米孔中受限流体的分子动力学中的应用
errFluid Phase Equilibria
IF2.7
err2025-11-28
err0
PREAI
errNikhil Muralidhar; Mohamed Mehana; Naren Ramakrishnan; Anuj Karpatne; Nicholas Lubbers
err分享
err收藏
GPU-Accelerated Graph-Based Semiempirical Quantum Chemistry
errJOURNAL OF CHEMICAL THEORY AND COMPUTATION
IF5.5
err2025-10-01
err0
PREAI
errKulichenko, Maksim; Stanton, Robert M.; Li, Cheng-Han; Lubbers, Nicholas; Tretiak, Sergei; Wall, Michael E.; Negre, Christian F. A.; Finkelstein, Joshua; Niklasson, Anders M. N.
err分享
err收藏
Multi-fidelity learning for interatomic potentials: low-level forces and high-level energies are all you need*多 fidelity 学习用于原子间势能：低级力和高级能量就是你所需要的*
errMachine Learning: Science and Technology
IF0
err2025-09-29
err0
errOAAI
errMitchell Messerly; Sakib Matin; Alice E A Allen; Benjamin Nebgen; Kipton Barros; Justin S Smith; Nicholas Lubbers; Richard Messerly
err分享
err收藏
Toward machine learning interatomic potentials for modeling uranium mononitride面向机器学习型原子间势能用于模拟一氮化铀
errMachine Learning: Science and Technology
IF0
err2025-09-24
err0
errOAAI
errLorena Alzate-Vargas; Kashi N Subedi; Nicholas Lubbers; Michael W D Cooper; Roxanne M Tutchton; Tammie Gibson; Richard A Messerly
err分享
err收藏
Teacher-student training improves the accuracy and efficiency of machine learning interatomic potentials师生训练提高了机器学习原子间势能的准确性和效率。
errDigital Discovery
IF5.6
err2025-08-07
err0
errOAAI
errSakib Matin; Alice E. A. Allen; Emily Shinkle; Aleksandra Pachalieva; Galen T. Craven; Benjamin Nebgen; Justin S. Smith; Richard Messerly; Ying Wai Li; Sergei Tretiak; Kipton Barros; Nicholas Lubbers
err分享
err收藏
Shadow Molecular Dynamics with a Machine Learned Flexible Charge Potential
errJOURNAL OF CHEMICAL THEORY AND COMPUTATION
IF5.5
err2025-03-01
err0
PREAI
errLi, Cheng-Han; Kaymak, Mehmet Cagri; Kulichenko, Maksim; Lubbers, Nicholas; Nebgen, Benjamin T.; Tretiak, Sergei; Finkelstein, Joshua; Tabor, Daniel P.; Niklasson, Anders M. N.
err分享
err收藏
MLTB: Enhancing Transferability and Extensibility of Density Functional Tight-Binding Theory with Many-body Interaction Corrections
errJOURNAL OF CHEMICAL THEORY AND COMPUTATION
IF5.5
err2025-01-29
err0
errOAAI
errBurrill, Daniel J.; Liu, Chang; Taylor, Michael G.; Cawkwell, Marc J.; Perez, Danny; Batista, Enrique R.; Lubbers, Nicholas; Yang, Ping
err分享
err收藏
Challenges and opportunities for machine learning potentials in transition path sampling: alanine dipeptide and azobenzene studies机器学习势在过渡路径采样中的挑战与机遇：丙氨酸二肽和偶氮苯研究
errDIGITAL DISCOVERY
IF5.6
err2025-01-01
err0
errOAAI
errFedik, Nikita; Li, Wei; Lubbers, Nicholas; Nebgen, Benjamin; Tretiak, Sergei; Li, Ying Wai
err分享
err收藏
Thermodynamic Transferability in Coarse-Grained Force Fields Using Graph Neural Networks使用图神经网络在粗粒度力场中的热力学可传递性
errJOURNAL OF CHEMICAL THEORY AND COMPUTATION
IF5.5
err2024-11-23
err1
errOAAI
errShinkle, Emily; Pachalieva, Aleksandra; Bahl, Riti; Matin, Sakib; Gifford, Brendan; Craven, Galen T.; Lubbers, Nicholas
err分享
err收藏
Learning together: Towards foundation models for machine learning interatomic potentials with meta-learning共同学习: 通过元学习建立机器学习的原子间势的基础模型
errNPJ COMPUTATIONAL MATERIALS
IF11.9
err2024-07-17
err3
errOAAI
errAllen, Alice E. A.; Lubbers, Nicholas; Matin, Sakib; Smith, Justin; Messerly, Richard; Tretiak, Sergei; Barros, Kipton
err分享
err收藏
Journey over destination: dynamic sensor placement enhances generalization
errMACHINE LEARNING-SCIENCE AND TECHNOLOGY
IF4.6
err2024-06-18
err1
errOAAI
errMarcato, Agnese; Guiltinan, Eric; Viswanathan, Hari; O'Malley, Daniel; Lubbers, Nicholas; Santos, Javier E.
err分享
err收藏
Learning a general model of single phase flow in complex 3D porous media学习复杂3D多孔介质中单相流的通用模型
errMACHINE LEARNING-SCIENCE AND TECHNOLOGY
IF4.6
err2024-05-10
err0
errOAAI
errSantos, Javier E.; Marcato, Agnese; Kang, Qinjun; Mehana, Mohamed; O'Malley, Daniel; Viswanathan, Hari; Lubbers, Nicholas
err分享
err收藏
Exploring the frontiers of condensed-phase chemistry with a general reactive machine learning potential探索具有一般反应性机器学习潜力的凝聚相化学的前沿
errNATURE CHEMISTRY
IF20.2
err2024-03-07
err22
errOAAI
errZhang, Shuhao; Makos, Malgorzata Z.; Jadrich, Ryan B.; Kraka, Elfi; Barros, Kipton; Nebgen, Benjamin T.; Tretiak, Sergei; Isayev, Olexandr; Lubbers, Nicholas; Messerly, Richard A.; Smith, Justin S.
err分享
err收藏
Machine Learning Potentials with the Iterative Boltzmann Inversion: Training to Experiment
errJOURNAL OF CHEMICAL THEORY AND COMPUTATION
IF5.5
err2024-02-02
err10
errOAAI
errMatin, Sakib; Allen, Alice E. A.; Smith, Justin; Lubbers, Nicholas; Jadrich, Ryan B.; Messerly, Richard; Nebgen, Benjamin; Li, Ying Wai; Tretiak, Sergei; Barros, Kipton
err分享
err收藏
Machine Learning Framework for Modeling Exciton Polaritons in Molecular Materials
errJOURNAL OF CHEMICAL THEORY AND COMPUTATION
IF5.5
err2024-01-03
err2
errOAAI
errLi, Xinyang; Lubbers, Nicholas; Tretiak, Sergei; Barros, Kipton; Zhang, Yu
err分享
err收藏
Linear graphlet models for accurate and interpretable cheminformatics
errDIGITAL DISCOVERY
IF5.6
err2024-01-01
err0
errOAAI
errTynes, Michael; Taylor, Michael G.; Janssen, Jan; Burrill, Daniel J.; Perez, Danny; Yang, Ping; Lubbers, Nicholas
err分享
err收藏
Development of the Senseiver for efficient field reconstruction from sparse observations
errNATURE MACHINE INTELLIGENCE
IF23.9
err2023-11-06
err13
errOAAI
errSantos, Javier E.; Fox, Zachary R.; Mohan, Arvind; O'Malley, Daniel; Viswanathan, Hari; Lubbers, Nicholas
err分享
err收藏
Predictive scale-bridging simulations through active learning
errSCIENTIFIC REPORTS
IF3.9
err2023-09-27
err1
errOAAI
errKarra, Satish; Mehana, Mohamed; Lubbers, Nicholas; Chen, Yu; Diaw, Abdourahmane; Santos, Javier E.; Pachalieva, Aleksandra; Pavel, Robert S.; Haack, Jeffrey R.; Mckerns, Michael; Junghans, Christoph; Kang, Qinjun; Livescu, Daniel; Germann, Timothy C.; Viswanathan, Hari S.
err分享
err收藏

研究方向

暂时未获取到该数据
合作学者
合作期刊
S
Sergei Tretiak
H 指数: 88 · 论文数: 738
A
Alexander I. Boldyrev
H 指数: 87 · 论文数: 558
Q
Qinjun Kang
H 指数: 70 · 论文数: 278
E
Elfi Kraka
H 指数: 66 · 论文数: 358
A
Adrián E. Roitberg
H 指数: 64 · 论文数: 321
查看更多