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Titlebook: Receptor/Ligand Sorting Along the Endocytic Pathway; Jennifer J. Linderman,Douglas A. Lauffenburger Book 1989 Springer-Verlag Berlin Heide

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樓主: Adentitious
31#
發(fā)表于 2025-3-26 21:04:45 | 只看該作者
32#
發(fā)表于 2025-3-27 03:07:33 | 只看該作者
when making the decisions. Online social networks have a problem with misinformation which is known to have negative effects. In this paper, we propose to utilize XAI techniques to study what factors lead to misinformation spreading by explaining a trained graph neural network that predicts misinfo
33#
發(fā)表于 2025-3-27 06:29:03 | 只看該作者
Jennifer J. Linderman,Douglas A. Lauffenburger when making the decisions. Online social networks have a problem with misinformation which is known to have negative effects. In this paper, we propose to utilize XAI techniques to study what factors lead to misinformation spreading by explaining a trained graph neural network that predicts misinfo
34#
發(fā)表于 2025-3-27 11:25:07 | 只看該作者
35#
發(fā)表于 2025-3-27 13:46:05 | 只看該作者
Jennifer J. Linderman,Douglas A. Lauffenburgerusal structure learning algorithms. GCA generates an explanatory graph from high-level human-interpretable features, revealing how these features affect each other and the black-box output. We show how these high-level features do not always have to be human-annotated, but can also be computationall
36#
發(fā)表于 2025-3-27 19:48:07 | 只看該作者
37#
發(fā)表于 2025-3-28 01:57:06 | 只看該作者
38#
發(fā)表于 2025-3-28 04:28:30 | 只看該作者
39#
發(fā)表于 2025-3-28 08:50:04 | 只看該作者
Jennifer J. Linderman,Douglas A. Lauffenburger the main idea of the explainable recommenders outlined with.The book proposes techniques, with an emphasis on the financial sector, which will make recommendation systems both accurate and explainable. The vast majority of AI models work like black box models. However, in many applications, e.g., m
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