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Titlebook: Epistemic Uncertainty in Artificial Intelligence ; First International Fabio Cuzzolin,Maryam Sultana Conference proceedings 2024 The Edito

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發(fā)表于 2025-3-26 23:19:09 | 只看該作者
https://doi.org/10.1007/978-1-4471-5460-0entation in autonomous driving. Our approach is based on the idea that deep learning-based perception for autonomous driving is uncertain and best represented as a probability distribution. As autonomous vehicles’ safety is paramount, it is crucial for perception systems to recognize when the vehicl
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發(fā)表于 2025-3-27 04:22:42 | 只看該作者
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發(fā)表于 2025-3-27 06:51:04 | 只看該作者
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發(fā)表于 2025-3-27 11:39:11 | 只看該作者
Analysis of Genetic Association Studiesy interacting with the environment. As the agent tries to improve on the policy present in the dataset, it can introduce distributional shift between the training data and the suggested agent’s policy which can lead to poor performance. To avoid the agent assigning high values to out-of-distribution
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發(fā)表于 2025-3-27 16:07:21 | 只看該作者
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發(fā)表于 2025-3-27 18:17:01 | 只看該作者
https://doi.org/10.1007/978-3-031-57963-9Epistemic Uncertainty; Bayesian Deep Learning; Probabilistic Machine Learning; Variational Autoencoder;
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發(fā)表于 2025-3-27 23:57:11 | 只看該作者
Conference proceedings 2024 The .8. full papers together included in this volume were carefully reviewed and selected from 16 submissions...Epistemic AI focuses, in particular, on some of the most important areas of machine learning: unsupervised learning, supervised learning, and reinforcement learning..
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