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

小虫

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

dura-mater

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

,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

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Parabola

Psa617

抱负

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

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