Ultra-Fast Evaluation of Protein Energies Directly from Sequence. - Gevorg Grigoryan; Fei Zhou 002; Steve R. Lustig; Gerbrand Ceder; Dane Morgan; Amy E. Keating (PLoS Comput. Biol., 2006)

Assessing Graph-based Deep Learning Models for Predicting Flash Point. - Xiaoyu Sun; Nathaniel J. Krakauer; Alexander Politowicz; Wei-Ting Chen; Qiying Li; Zuoyi Li; Xianjia Shao; Alfred Sunaryo; Mingren Shen; James Wang; Dane Morgan (CoRR, 2020)

Exploring Generative Adversarial Networks for Image-to-Image Translation in STEM Simulation. - Nick Lawrence; Mingren Shen; Ruiqi Yin; Cloris Feng; Dane Morgan (CoRR, 2020)

A Deep Learning Based Automatic Defect Analysis Framework for In-situ TEM Ion Irradiations. - Mingren Shen; Guanzhao Li; Dongxia Wu; Yudai Yaguchi; Jack C. Haley; Kevin G. Field; Dane Morgan (CoRR, 2021)

Multi defect detection and analysis of electron microscopy images with deep learning. - Mingren Shen; Guanzhao Li; Dongxia Wu; Yuhan Liu; Jacob Greaves; Wei Hao; Nathaniel J. Krakauer; Leah Krudy; Jacob Perez; Varun Sreenivasan; Bryan Sanchez; Oigimer Torres; et al. (CoRR, 2021)

Performance, Successes and Limitations of Deep Learning Semantic Segmentation of Multiple Defects in Transmission Electron Micrographs. - Ryan Jacobs; Mingren Shen; Yuhan Liu; Wei Hao; Xiaoshan Li; Ruoyu He; Jacob R. C. Greaves; Donglin Wang; Zeming Xie; Zitong Huang; Chao Wang; Kevin G. Field; et al. (CoRR, 2021)

Machine learning for interpreting coherent X-ray speckle patterns. - Mingren Shen; Dina Sheyfer; Troy David Loeffler; Subramanian K. R. S. Sankaranarayanan; G. Brian Stephenson; Maria K. Y. Chan; Dane Morgan (CoRR, 2022)

Data for: Impact of Non-Uniform Thermionic Emission on the Transition Behavior between Temperature- and Space-Charge-Limited Emission. - Dongzheng Chen; Ryan Jacobs; Dane Morgan; John Booske (IEEE DataPort, 2022)

Flexible, Model-Agnostic Method for Materials Data Extraction from Text Using General Purpose Language Models. - Maciej P. Polak; Shrey Modi; Anna Latosinska; Jinming Zhang; Ching-Wen Wang; Shanonan Wang; Ayan Deep Hazra; Dane Morgan (CoRR, 2023)

Extracting Accurate Materials Data from Research Papers with Conversational Language Models and Prompt Engineering - Example of ChatGPT. - Maciej P. Polak; Dane Morgan (CoRR, 2023)

Role of multifidelity data in sequential active learning materials discovery campaigns: case study of electronic bandgap. - Ryan Jacobs; Philip E. Goins; Dane Morgan (Mach. Learn. Sci. Technol., 2023)

Accelerating Ensemble Error Bar Prediction with Single Models Fits. - Vidit Agrawal; Shixin Zhang; Lane E. Schultz; Dane Morgan (CoRR, 2024)

Determining Domain of Machine Learning Models using Kernel Density Estimates: Applications in Materials Property Prediction. - Lane E. Schultz; Yiqi Wang; Ryan Jacobs; Dane Morgan (CoRR, 2024)

Accelerating Domain-Aware Electron Microscopy Analysis Using Deep Learning Models with Synthetic Data and Image-Wide Confidence Scoring. - Matthew J. Lynch; Ryan Jacobs; Gabriella Bruno; Priyam Patki; Dane Morgan; Kevin G. Field (CoRR, 2024)

Regression with Large Language Models for Materials and Molecular Property Prediction. - Ryan Jacobs; Maciej P. Polak; Lane E. Schultz; Hamed Mahdavi; Vasant G. Honavar; Dane Morgan (CoRR, 2024)

Beyond designer's knowledge: Generating materials design hypotheses via large language models. - Quanliang Liu; Maciej P. Polak; So Yeon Kim; MD Al Amin Shuvo; Hrishikesh Shridhar Deodhar; Jeongsoo Han; Dane Morgan; Hyunseok Oh (CoRR, 2024)

Foundry-ML (latest). - K. J. Schmidt; Aristana Scourtas; Logan T. Ward; Steve Wangen; Marcus Schwarting; Isaac Darling; Ethan Truelove; Aadit Ambadkar; Ribhav Bose; Zoa Katok; Jingrui Wei; Xiangguo Li; et al. (Zenodo, 2024)

Foundry-ML - Software and Services to Simplify Access to Machine Learning Datasets in Materials Science. - K. J. Schmidt; Aristana Scourtas; Logan T. Ward; Steve Wangen; Marcus Schwarting; Isaac Darling; Ethan Truelove; Aadit Ambadkar; Ribhav Bose; Zoa Katok; Jingrui Wei; Xiangguo Li; et al. (Zenodo, 2024)

Foundry-ML - Software and Services to Simplify Access to Machine Learning Datasets in Materials Science. - K. J. Schmidt; Aristana Scourtas; Logan T. Ward; Steve Wangen; Marcus Schwarting; Isaac Darling; Ethan Truelove; Aadit Ambadkar; Ribhav Bose; Zoa Katok; Jingrui Wei; Xiangguo Li; et al. (Zenodo, 2024)

Foundry-ML - Software and Services to Simplify Access to Machine Learning Datasets in Materials Science. - K. J. Schmidt; Aristana Scourtas; Logan T. Ward; Steve Wangen; Marcus Schwarting; Isaac Darling; Ethan Truelove; Aadit Ambadkar; Ribhav Bose; Zoa Katok; Jingrui Wei; Xiangguo Li; et al. (Zenodo, 2024)

Foundry-ML - Software and Services to Simplify Access to Machine Learning Datasets in Materials Science. - K. J. Schmidt; Aristana Scourtas; Logan T. Ward; Steve Wangen; Marcus Schwarting; Isaac Darling; Ethan Truelove; Aadit Ambadkar; Ribhav Bose; Zoa Katok; Jingrui Wei; Xiangguo Li; et al. (J. Open Source Softw., 2024)

Predicting Performance of Object Detection Models in Electron Microscopy Using Random Forests. - Ni Li; Ryan Jacobs; Matthew J. Lynch; Vidit Agrawal; Kevin G. Field; Dane Morgan (CoRR, 2025)

A practical guide to machine learning interatomic potentials - Status and future. - Ryan Jacobs; Dane Morgan; Siamak Attarian; Jun Meng; Chen Shen; Zhenghao Wu; Clare Yijia Xie; Julia H. Yang; Nongnuch Artrith; Ben Blaiszik; Gerbrand Ceder; Kamal Choudhary; et al. (CoRR, 2025)

Leveraging Vision Capabilities of Multimodal LLMs for Automated Data Extraction from Plots. - Maciej P. Polak; Dane Morgan (CoRR, 2025)

Physical regularized Hierarchical Generative Model for Metallic Glass Structural Generation and Energy Prediction. - Qiyuan Chen; Ajay Annamareddy; Ying-Fei Li; Dane Morgan; Bu Wang (CoRR, 2025)