MAP

Ata Madanchi1, Lena Simine2

  • 1Department of Physics, McGill University, 3600 University St., Montreal, Quebec H3A 2T8, Canada.

PubMed
まとめ

私たちは,静的構造を分析することによって,超冷却液体の動的異質性を診断するために,無監督の機械学習モデルであるMAPを導入します. MAPは,希少なダイナミックな出来事を,局所的な構造変化と結びつけ,ガラスの元ダイナミクスの直感的な特徴を提示します.

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