小虫
发表于 2025-3-25 03:34:48
0302-9743 rticular, on some of the most important areas of machine learning: unsupervised learning, supervised learning, and reinforcement learning..978-3-031-57962-2978-3-031-57963-9Series ISSN 0302-9743 Series E-ISSN 1611-3349
亲爱
发表于 2025-3-25 10:48:58
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dura-mater
发表于 2025-3-25 14:59:23
Laminated Glass Subjected to Blast Load,tors within the latent space and link the uncertainty to corresponding semantic factors for an explanation. The proposed techniques can also enhance explainable out-of-distribution (OOD) detection. We can not only identify OOD samples via their uncertainty, but also provide reasoning rooted in a semantic concept.
白杨鱼
发表于 2025-3-25 19:44:10
,A Novel Bayes’ Theorem for Upper Probabilities,n for this upper bound to become an equality. This result is interesting on its own, and has the potential of being applied to various fields of engineering (e.g. model predictive control), machine learning, and artificial intelligence.
Cloudburst
发表于 2025-3-25 23:32:20
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上坡
发表于 2025-3-26 02:34:02
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Parabola
发表于 2025-3-26 06:28:12
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Psa617
发表于 2025-3-26 08:47:23
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抱负
发表于 2025-3-26 15:12:52
https://doi.org/10.1007/978-1-4419-6947-7 models have emerged as the state-of-the-art approach for disease mapping since they are able to both capture structure in the data and robustly characterise uncertainty. When working with areal data, e.g. aggregates at the administrative unit level such as district or province, current models rely
exceed
发表于 2025-3-26 16:49:02
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