财主 发表于 2025-3-26 22:53:14

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Ascribe 发表于 2025-3-27 02:49:22

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dapper 发表于 2025-3-27 06:40:06

Melissa D. Lehti-Shiu,Cheng Zou,Shin-Han Shiune learning practitioners to understand the current techniqu.This book provides a full presentation of the current concepts and available techniques to make “machine learning” systems more explainable. The approaches presented can be applied to almost all the current “machine learning” models: linea

certain 发表于 2025-3-27 11:56:21

Yvonne Stahl,Rüdiger Simonne learning practitioners to understand the current techniqu.This book provides a full presentation of the current concepts and available techniques to make “machine learning” systems more explainable. The approaches presented can be applied to almost all the current “machine learning” models: linea

padding 发表于 2025-3-27 15:31:19

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AXIOM 发表于 2025-3-27 20:53:17

Thomas Bollerble artificial intelligence, such as the need to make the AI models interpretable, how black box machine/deep learning models can be understood using various XAI methods, different evaluation metrics for XAI, human-centered explainable AI, and applications of explainable AI in health care, security

IST 发表于 2025-3-27 22:48:05

Jia Li,Junbo Du,Kai He,Xiaoping Gounosed. The user either owns the training data and computing resources to train an interpretable model herself or owns a full access to an already trained model to be interpreted post-hoc. In this chapter, we consider a less investigated scenario of diagnosing ., where the user can only send queries

Adrenaline 发表于 2025-3-28 03:06:42

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陈腐思想 发表于 2025-3-28 07:46:57

Bruce D. Kohorn,Susan L. Kohorntanding the method in which the model relates text with visual concepts by synthesizing them. Deep generative models have been successfully employed to address this task, which formulates the problem as a translation task from text to image. However, learning a direct mapping from text to image is c

Stable-Angina 发表于 2025-3-28 12:36:50

Emily Indriolo,Daphne R. Goringing factor for a broader adoption of AI technology is the inherent risks that come with giving up human control and oversight to “intelligent” machines. For sensitive tasks involving critical infrastructures and affecting human well-being or health, it is crucial to limit the possibility of improper
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查看完整版本: Titlebook: Receptor-like Kinases in Plants; From Development to Frans Tax,Birgit Kemmerling Book 2012 Springer-Verlag Berlin Heidelberg 2012 primary