Amanda S. Barnard - researchr alias

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Viewing Publication 1 - 13 from 13

2024

Online meta-learned gradient norms for active learning in science and technologyHaiqi Dong, Amanda S. Barnard, Amanda J. Parker. mlst, 5(1):15041, March 2024. [doi]

2023

2022

Federated data processing and learning for collaboration in the physical sciencesW. Huang, Amanda S. Barnard. mlst, 3(4):45023, December 2022. [doi]

The impact of domain-driven and data-driven feature selection on the inverse design of nanoparticle catalystsSichao Li, Jonathan Y. C. Ting, Amanda S. Barnard. jocs, 65:101896, 2022. [doi]

Optimization-Free Inverse Design of High-Dimensional Nanoparticle Electrocatalysts Using Multi-target Machine LearningSichao Li, Jonathan Y. C. Ting, Amanda S. Barnard. iccs 2022: 307-318 [doi]

2021

Fast derivation of Shapley based feature importances through feature extraction methods for nanoinformaticsTommy Liu, Amanda S. Barnard. mlst, 2(3):35034, 2021. [doi]

2017

On reverse Monte Carlo constraints and model reproductionGeorge Opletal, Timothy C. Petersen, Amanda S. Barnard, Salvy P. Russo. jcc, 38(17):1547-1551, 2017. [doi]

Machine Learning for Silver Nanoparticle Electron Transfer Property PredictionBaichuan Sun, Michael Fernández, Amanda S. Barnard. jcisd, 57(10):2413-2423, October 2017. [doi]

2015

Quantitative Structure-Property Relationship Modeling of Electronic Properties of Graphene Using Atomic Radial Distribution Function ScoresMichael Fernández, Hongqing Shi, Amanda S. Barnard. jcisd, 55(12):2500-2506, 2015. [doi]

2011

Useful equations for modeling the relative stability of common nanoparticle morphologiesAmanda S. Barnard. cphysics, 182(1):11-13, 2011. [doi]

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