Learning from Correlations Based on Local Structure: Rare-Earth Nickelates Revisited. - Nicholas Wagner; Danilo Puggioni; James M. Rondinelli (J. Chem. Inf. Model., 2018)

Exploiting Colorimetry for Fidelity in Data Visualization. - Michael J. Waters; Jessica M. Walker; Christopher T. Nelson; Derek Joester; James M. Rondinelli (CoRR, 2020)

ET-AL: Entropy-Targeted Active Learning for Bias Mitigation in Materials Data. - Hengrui Zhang; Wei Wayne Chen; James M. Rondinelli; Wei Chen 041 (CoRR, 2022)

MolSets: Molecular Graph Deep Sets Learning for Mixture Property Modeling. - Hengrui Zhang; Jie Chen; James M. Rondinelli; Wei Chen 041 (CoRR, 2023)

Do Graph Neural Networks Work for High Entropy Alloys? - Hengrui Zhang; Ruishu Huang; Jie Chen; James M. Rondinelli; Wei Chen (CoRR, 2024)

Emerging Microelectronic Materials by Design: Navigating Combinatorial Design Space with Scarce and Dispersed Data. - Hengrui Zhang; Alexandru B. Georgescu; Suraj Yerramilli; Christopher Karpovich; Daniel W. Apley; Elsa A. Olivetti; James M. Rondinelli; Wei Chen 041 (CoRR, 2024)

Graph representation of local environments for learning high-entropy alloy properties. - Hengrui Zhang; Ruishu Huang; Jie Chen; James M. Rondinelli; Wei Chen 041 (Mach. Learn. Sci. Technol., 2025)

AI-Accelerated Electronic Materials Discovery and Development. - Christopher C. Price; Ichiro Takeuchi; James M. Rondinelli; Wei Chen 041; Christopher L. Hinkle (Computer, 2025)