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Titlebook: Artificial Intelligence for Scientific Discoveries; Extracting Physical Raban Iten Book 2023 The Editor(s) (if applicable) and The Author(

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樓主: 難受
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發(fā)表于 2025-3-23 09:43:36 | 只看該作者
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發(fā)表于 2025-3-23 16:22:33 | 只看該作者
Book 2023ering physical concepts with machine learning and elucidates their strengths and limitations. The?automation?of the creation of experimental setups and physical models, as well as model testing are discussed. The focus of the book is the?automation?of an important step of the model creation, namely
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發(fā)表于 2025-3-23 20:49:05 | 只看該作者
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發(fā)表于 2025-3-24 01:01:08 | 只看該作者
Artificial Intelligence for Scientific DiscoveriesExtracting Physical
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發(fā)表于 2025-3-24 03:38:05 | 只看該作者
Artificial Intelligence for Scientific Discoveries978-3-031-27019-2
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發(fā)表于 2025-3-24 06:44:50 | 只看該作者
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發(fā)表于 2025-3-24 14:25:37 | 只看該作者
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發(fā)表于 2025-3-24 16:33:38 | 只看該作者
978-3-031-27021-5The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
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發(fā)表于 2025-3-24 21:55:42 | 只看該作者
https://doi.org/10.1007/978-3-030-67877-7ual information from it. The chapter stresses the significance of comprehending how AI makes its predictions to gain insights into fundamental problems in modern physics. Furthermore, the chapter provides motivation for the following chapters and offers an overview of what to expect from the book.
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發(fā)表于 2025-3-25 00:14:45 | 只看該作者
Fallacies in Medicine and Healthch networks and why they often generalize well to data not seen during the training. Therefore, we focus on a basic understanding of what neural networks are and how the training method works in principle.
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