Reply to: Comment on “Machine learning enhanced analysis of EBSD data for texture representation”

J. Wanni; C. A. Bronkhorst; D. J. Thoma

doi:10.1038/s41524-025-01562-0

Reply to: Comment on “Machine learning enhanced analysis of EBSD data for texture representation”

J. Wanni
, C. A. Bronkhorst
, D. J. Thoma

Research output: Contribution to journal › Letter › peer-review

Abstract

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.

Original language	English
Article number	73
Journal	npj Computational Materials
Volume	11
Issue number	1
DOIs	https://doi.org/10.1038/s41524-025-01562-0
State	Published - Dec 2025
Externally published	Yes

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@article{533e6de989b74b1f9f43f8ab03473ad8,

title = "Reply to: Comment on “Machine learning enhanced analysis of EBSD data for texture representation”",

abstract = "We respond to Schaeben et al.{\textquoteright}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{\textquoteright} practical performance.",

author = "J. Wanni and Bronkhorst, \{C. A.\} and Thoma, \{D. J.\}",

year = "2025",

month = dec,

doi = "10.1038/s41524-025-01562-0",

language = "English",

volume = "11",

journal = "npj Computational Materials",

number = "1",

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TY - JOUR

T1 - Reply to: Comment on “Machine learning enhanced analysis of EBSD data for texture representation”

AU - Wanni, J.

AU - Bronkhorst, C. A.

AU - Thoma, D. J.

PY - 2025/12

Y1 - 2025/12

N2 - 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.

AB - 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.

UR - https://www.scopus.com/pages/publications/105000449033

U2 - 10.1038/s41524-025-01562-0

DO - 10.1038/s41524-025-01562-0

M3 - Letter

VL - 11

JO - npj Computational Materials

JF - npj Computational Materials

IS - 1

M1 - 73

ER -

Reply to: Comment on “Machine learning enhanced analysis of EBSD data for texture representation”

Abstract

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