Dane Morgan - RankMe

22 papers A* 1Journal 21

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	Physical-regularized Hierarchical Generative Model for Metallic Glass Structural Generation and Energy Prediction. AAAI Qiyuan Chen, Ajay Annamareddy, Ying-Fei Li, Dane Morgan, Bu Wang
2025	J	`jnl`	A practical guide to machine learning interatomic potentials - Status and future. CoRR 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, Gábor Csányi, Ekin Dogus Cubuk, Bowen Deng, Ralf Drautz, Xiang Fu, Jonathan Godwin, Vasant G. Honavar, Olexandr Isayev, Anders Johansson, Boris Kozinsky, Stefano Martiniani, Shyue Ping Ong, Igor Poltavsky, K. J. Schmidt, So Takamoto, Aidan Thompson, Julia Westermayr, Brandon M. Wood
2025	J	`jnl`	Leveraging Vision Capabilities of Multimodal LLMs for Automated Data Extraction from Plots. CoRR Maciej P. Polak, Dane Morgan
2025	J	`jnl`	Physical regularized Hierarchical Generative Model for Metallic Glass Structural Generation and Energy Prediction. CoRR Qiyuan Chen, Ajay Annamareddy, Ying-Fei Li, Dane Morgan, Bu Wang
2025	J	`jnl`	Predicting Performance of Object Detection Models in Electron Microscopy Using Random Forests. CoRR Ni Li, Ryan Jacobs, Matthew J. Lynch, Vidit Agrawal, Kevin G. Field, Dane Morgan
2024	J	`jnl`	Accelerating Domain-Aware Electron Microscopy Analysis Using Deep Learning Models with Synthetic Data and Image-Wide Confidence Scoring. CoRR Matthew J. Lynch, Ryan Jacobs, Gabriella Bruno, Priyam Patki, Dane Morgan, Kevin G. Field
2024	J	`jnl`	Accelerating Ensemble Error Bar Prediction with Single Models Fits. CoRR Vidit Agrawal, Shixin Zhang, Lane E. Schultz, Dane Morgan
2024	J	`jnl`	Beyond designer's knowledge: Generating materials design hypotheses via large language models. CoRR Quanliang Liu, Maciej P. Polak, So Yeon Kim, MD Al Amin Shuvo, Hrishikesh Shridhar Deodhar, Jeongsoo Han, Dane Morgan, Hyunseok Oh
2024	J	`jnl`	Determining Domain of Machine Learning Models using Kernel Density Estimates: Applications in Materials Property Prediction. CoRR Lane E. Schultz, Yiqi Wang, Ryan Jacobs, Dane Morgan
2024	J	`jnl`	Foundry-ML - Software and Services to Simplify Access to Machine Learning Datasets in Materials Science. J. Open Source Softw. 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, Ryan Jacobs, Lane Schultz, Doyeon Kim, Michael C. Ferris, Paul M. Voyles, Dane Morgan, Ian T. Foster, Ben Blaiszik
2024	J	`jnl`	Machine learning materials properties with accurate predictions, uncertainty estimates, domain guidance, and persistent online accessibility. Mach. Learn. Sci. Technol. Ryan Jacobs, Lane E. Schultz, Aristana Scourtas, K. J. Schmidt, Owen Price Skelly, Will Engler, Ian T. Foster, Ben Blaiszik, Paul M. Voyles, Dane Morgan
2024	J	`jnl`	Regression with Large Language Models for Materials and Molecular Property Prediction. CoRR Ryan Jacobs, Maciej P. Polak, Lane E. Schultz, Hamed Mahdavi, Vasant G. Honavar, Dane Morgan
2023	J	`jnl`	Extracting Accurate Materials Data from Research Papers with Conversational Language Models and Prompt Engineering - Example of ChatGPT. CoRR Maciej P. Polak, Dane Morgan
2023	J	`jnl`	Flexible, Model-Agnostic Method for Materials Data Extraction from Text Using General Purpose Language Models. CoRR Maciej P. Polak, Shrey Modi, Anna Latosinska, Jinming Zhang, Ching-Wen Wang, Shanonan Wang, Ayan Deep Hazra, Dane Morgan
2023	J	`jnl`	Role of multifidelity data in sequential active learning materials discovery campaigns: case study of electronic bandgap. Mach. Learn. Sci. Technol. Ryan Jacobs, Philip E. Goins, Dane Morgan
2022	J	`jnl`	Machine learning for interpreting coherent X-ray speckle patterns. CoRR Mingren Shen, Dina Sheyfer, Troy David Loeffler, Subramanian K. R. S. Sankaranarayanan, G. Brian Stephenson, Maria K. Y. Chan, Dane Morgan
2021	J	`jnl`	A Deep Learning Based Automatic Defect Analysis Framework for In-situ TEM Ion Irradiations. CoRR Mingren Shen, Guanzhao Li, Dongxia Wu, Yudai Yaguchi, Jack C. Haley, Kevin G. Field, Dane Morgan
2021	J	`jnl`	Multi defect detection and analysis of electron microscopy images with deep learning. CoRR 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, Wei Li, Kevin Field, Dane Morgan
2021	J	`jnl`	Performance, Successes and Limitations of Deep Learning Semantic Segmentation of Multiple Defects in Transmission Electron Micrographs. CoRR 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, Dane Morgan
2020	J	`jnl`	Assessing Graph-based Deep Learning Models for Predicting Flash Point. CoRR Xiaoyu Sun, Nathaniel J. Krakauer, Alexander Politowicz, Wei-Ting Chen, Qiying Li, Zuoyi Li, Xianjia Shao, Alfred Sunaryo, Mingren Shen, James Wang, Dane Morgan
2020	J	`jnl`	Exploring Generative Adversarial Networks for Image-to-Image Translation in STEM Simulation. CoRR Nick Lawrence, Mingren Shen, Ruiqi Yin, Cloris Feng, Dane Morgan
2006	J	`jnl`	Ultra-Fast Evaluation of Protein Energies Directly from Sequence. PLoS Comput. Biol. Gevorg Grigoryan, Fei Zhou, Steve R. Lustig, Gerbrand Ceder, Dane Morgan, Amy E. Keating