Interpretable multi-objective machine learning with calibrated uncertainty for deployment-oriented prediction of defects and properties in polymer FFF
2025MeasurementJournal
10.1016/j.measurement.2025.119350Full text1 citations
2025MeasurementJournal
10.1016/j.measurement.2025.119350Full text1 citations
5 authors across 4 institutions in 3 countries.
Assignment is probabilistic — a work belongs to several fields in proportions.
Several sources describing one work is the point — it means the record rests on more than one authority.
2025 · Measurement · 1 citations
https://openalex.org/W4415313010