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Titlebook: Deep Learning and Physics; Akinori Tanaka,Akio Tomiya,Koji Hashimoto Book 2021 The Editor(s) (if applicable) and The Author(s), under excl

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發(fā)表于 2025-3-25 06:56:41 | 只看該作者
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發(fā)表于 2025-3-25 09:49:46 | 只看該作者
Petteri Packalén,Matti Maltamo,Timo Tokolaoto) are also co-authors of research papers in this interdisciplinary field. Collaborative research is something that is only fun if people who share the same ambition but have different backgrounds gather. We guess that readers have started reading this book with various motivations, but in fact, a
23#
發(fā)表于 2025-3-25 12:39:57 | 只看該作者
Akinori Tanaka,Akio Tomiya,Koji HashimotoIs the first machine learning textbook written by physicists so that physicists and undergraduates can learn easily.Presents applications to physics problems written so that readers can soon imagine h
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發(fā)表于 2025-3-25 16:44:44 | 只看該作者
Mathematical Physics Studieshttp://image.papertrans.cn/d/image/264597.jpg
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發(fā)表于 2025-3-25 22:36:19 | 只看該作者
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發(fā)表于 2025-3-26 01:44:38 | 只看該作者
https://doi.org/10.1007/978-1-4419-0941-1 the words of physics in the previous chapter. A convolutional neural network has a structure that emphasizes the spatial proximity in input data. Also, recurrent neural networks have a structure to learn input data in time series. You will learn how to provide a network structure that respects the characteristics of data.
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發(fā)表于 2025-3-26 06:51:06 | 只看該作者
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發(fā)表于 2025-3-26 20:01:57 | 只看該作者
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