Reply to: Comment on “Machine learning enhanced analysis of EBSD data for texture representation”
We respond to Schaeben et al.’s1 comment on our paper, “Machine Learning Enhanced Analysis of EBSD Data for Texture Representation.” While their observations are factually correct, they do not disprove our results. Our method, TACS, preserves the full distribution of crystallographic orientations and is validated with real-world data. We emphasize the importance of empirical validation over theoretical constructs in assessing machine learning methods’ practical performance.
Authors
- Curt A. Bronkhorst (ORCID: https://orcid.org/0000-0002-2709-1964)
- J. Wanni (ORCID: https://orcid.org/0000-0002-4417-1536)
- Dan J. Thoma (ORCID: https://orcid.org/0000-0001-5807-3219)
Institutions
- University of Wisconsin–Madison (US)
Publication Details
- Journal
- npj Computational Materials
- Published
- 2025-03-17
- DOI
- https://doi.org/10.1038/s41524-025-01562-0
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- U.S. Department of Defense