Amanda S. Barnard

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 19

Top Topics

Distribution Function

Actionable Knowledge Discovery

Machine Learning

Top Venues

Mach. Learn. Sci. Technol.

J. Chem. Inf. Model.

J. Comput. Sci.

Publications

Zixin Zhuang, Amanda S. Barnard
Classification of battery compounds using structure-free Mendeleev encodings. J. Cheminformatics 16 (1) (2024)
Sichao Li, Amanda S. Barnard, Quanling Deng
Practical Attribution Guidance for Rashomon Sets. CoRR (2024)
Haiqi Dong, Amanda S. Barnard, Amanda J. Parker
Online meta-learned gradient norms for active learning in science and technology. Mach. Learn. Sci. Technol. 5 (1) (2024)
Sichao Li, Amanda S. Barnard
Diverse Explanations from Data-driven and Domain-driven Perspectives for Machine Learning Models. CoRR (2024)
Sichao Li, Rong Wang, Quanling Deng, Amanda S. Barnard
Exploring the cloud of feature interaction scores in a Rashomon set. ICLR (2024)
Sichao Li, Rong Wang, Quanling Deng, Amanda S. Barnard
Exploring the cloud of feature interaction scores in a Rashomon set. CoRR (2023)
Tommy Liu, Amanda S. Barnard
Shapley Based Residual Decomposition for Instance Analysis. ICML (2023)
Yufan Xia, Marco De La Pierre, Amanda S. Barnard, Giuseppe M. J. Barca
A Machine Learning Approach Towards Runtime Optimisation of Matrix Multiplication. IPDPS (2023)
Sichao Li, Amanda S. Barnard
Variance Tolerance Factors For Interpreting All Neural Networks. IJCNN (2023)
Weitong Huang, Hanna Suominen, Tommy Liu, Gregory Rice, Carlos Salomon, Amanda S. Barnard
Explainable discovery of disease biomarkers: The case of ovarian cancer to illustrate the best practice in machine learning and Shapley analysis. J. Biomed. Informatics 141 (2023)
Tommy Liu, Amanda S. Barnard
Shapley Based Residual Decomposition for Instance Analysis. CoRR (2023)
Sichao Li, Jonathan Y. C. Ting, Amanda S. Barnard
The impact of domain-driven and data-driven feature selection on the inverse design of nanoparticle catalysts. J. Comput. Sci. 65 (2022)
W. Huang, Amanda S. Barnard
Federated data processing and learning for collaboration in the physical sciences. Mach. Learn. Sci. Technol. 3 (4) (2022)
Sichao Li, Amanda S. Barnard
Variance Tolerance Factors For Interpreting Neural Networks. CoRR (2022)
Sichao Li, Jonathan Y. C. Ting, Amanda S. Barnard
Optimization-Free Inverse Design of High-Dimensional Nanoparticle Electrocatalysts Using Multi-target Machine Learning. ICCS (1) (2022)
Tommy Liu, Amanda S. Barnard
Fast derivation of Shapley based feature importances through feature extraction methods for nanoinformatics. Mach. Learn. Sci. Technol. 2 (3) (2021)
Baichuan Sun, Michael Fernández, Amanda S. Barnard
Machine Learning for Silver Nanoparticle Electron Transfer Property Prediction. J. Chem. Inf. Model. 57 (10) (2017)
George Opletal, Timothy C. Petersen, Amanda S. Barnard, Salvy P. Russo
On reverse Monte Carlo constraints and model reproduction. J. Comput. Chem. 38 (17) (2017)
Michael Fernández, Hongqing Shi, Amanda S. Barnard
Quantitative Structure-Property Relationship Modeling of Electronic Properties of Graphene Using Atomic Radial Distribution Function Scores. J. Chem. Inf. Model. 55 (12) (2015)
Amanda S. Barnard
Useful equations for modeling the relative stability of common nanoparticle morphologies. Comput. Phys. Commun. 182 (1) (2011)