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Updated: Sep 9, 2025

Phase Diagram Characterization Using Magnetic Beads as Liquid Carriers
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Published on: September 4, 2015

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PINNでの学習:フェーズ移行,拡散均衡,および一般化

Sokratis J Anagnostopoulos1, Juan Diego Toscano2, Nikolaos Stergiopulos1

  • 1Laboratory of Hemodynamics and Cardiovascular Technology, EPFL, Lausanne, 1015, VD, Switzerland.

Neural networks : the official journal of the International Neural Network Society
|August 30, 2025
PubMed
まとめ

ニューラルネットワークの訓練において グラデーションが並べられ 安定した収束に至る 新しい"拡散均衡"の段階を 特定しました この段階は,均質な残量と組み合わせると,モデルの一般化を促進し,学習を加速します.

キーワード:
一般化グラデーションストキャスティシティ情報ボトルネック理論PINNsのフェーズ移行残った均質性

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