A Formation Energy Predictor for Crystalline Materials Using Ensemble Data Mining. - Ankit Agrawal 001; Bryce Meredig; Chris Wolverton; Alok N. Choudhary (ICDM Workshops, 2016)

Building Data-driven Models with Microstructural Images: Generalization and Interpretability. - Julia Ling; Maxwell Hutchinson; Erin Antono; Brian DeCost; Elizabeth A. Holm; Bryce Meredig (CoRR, 2017)

Overcoming data scarcity with transfer learning. - Maxwell L. Hutchinson; Erin Antono; Brenna M. Gibbons; Sean Paradiso; Julia Ling; Bryce Meredig (CoRR, 2017)

Machine-learned metrics for predicting the likelihood of success in materials discovery. - Yoolhee Kim; Edward Kim; Erin Antono; Bryce Meredig; Julia Ling (CoRR, 2019)

ACED: Accelerated Computational Electrochemical systems Discovery. - Rachel C. Kurchin; Eric Muckley; Lance Kavalsky; Vinay I. Hegde; Dhairya Gandhi; Xiaoyu Sun; Matthew Johnson; Alan Edelman; James E. Saal; Christopher Vincent Rackauckas; Bryce Meredig; Viral B. Shah; et al. (CoRR, 2020)

Interpretable models for extrapolation in scientific machine learning. - Eric S. Muckley; James E. Saal; Bryce Meredig; Christopher S. Roper; John H. Martin (CoRR, 2022)