cond-mat.mtrl-sci · 2026-06-11 · No. 20

Materials Science, 2026-06-11.

1 new papers in cond-mat.mtrl-sci. Titles, authors, abstracts. Links to arXiv. Want this in your inbox every morning? Subscribe →

01 — The papers

1 entries
  1. 01

    Modelling magnetic material properties with uncertainty-aware neural networks

    Clemens Wager, Heisam Moustafa, Alexander Kovacs, Qais Ali, Harald Oezelt, Hayate Yamano, Masao Yano, Noritsugu...

    cond-mat.mtrl-sci · cs.LG

    Machine learning is increasingly applied to accelerate the discovery of novel materials by exploring large compositional and structural design spaces. Yet, the scarcity of high-quality data and the frequent need for out-of-distribution prediction introduce substantial uncertainty, making the assessment of model reliability essential. In this work, we investigate uncertainty quantification as a means to evaluate model confidence in the context...

    arxiv.org/abs/2606.11870 · PDF

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