Results 31 to 40 of about 5,037,515 (156)
Performance optimization scheme of turboshaft aeroengine based on Bayesian network
Xibei Gongye Daxue Xuebao, 2021 The turboshaft aeroengine is mainly used in helicopters. As a power device that drives the rotor to generate lift and propulsion, it has been rapidly developed in recent years. The manufacturing process of turboshaft aeroengine is complex, and there is a
doaj +1 more source
Opinion Dynamics with Bayesian Learning
Complexity, 2020 Bayesian learning is a rational and effective strategy in the opinion dynamic process. In this paper, we theoretically prove that individual Bayesian learning can realize asymptotic learning and we test it by simulations on the Zachary network.
Aili Fang +3 more
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Digital Health, 2022 Background Community-acquired pneumonia is one of the most common infectious diseases in children and is a leading cause of death among children under 5 years of age, resulting in high rates of antibiotic usage and hospitalization.
Jing Li +10 more
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Bayesian U-Net: Estimating Uncertainty in Semantic Segmentation of Earth Observation Images
Remote Sensing, 2021 In recent years, numerous deep learning techniques have been proposed to tackle the semantic segmentation of aerial and satellite images, increase trust in the leaderboards of main scientific contests and represent the current state-of-the-art ...
Clément Dechesne +2 more
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Application of Data Mining Using Bayesian Belief Network To Classify Quality of Web Services [PDF]
, 2013 In this paper, we employed Naïve Bayes, Augmented Naïve Bayes, Tree Augmented Naïve Bayes, Sons & Spouses, Markov Blanket, Augmented Markov Blanket, Semi Supervised and Bayesian network techniques to rank web services.
A, Govardhan +7 more
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Widening Access to Bayesian Problem Solving
Frontiers in Psychology, 2020 Bayesian reasoning and decision making is widely considered normative because it minimizes prediction error in a coherent way. However, it is often difficult to apply Bayesian principles to complex real world problems, which typically have many unknowns ...
Nicole Cruz +8 more
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Bayesian network classifiers in Weka [PDF]
, 2004 Various Bayesian network classifier learning algorithms are implemented in Weka [10].This note provides some user documentation and implementation details.
Remco R. Bouckaert, Bouckaert, Remco R.
core
IntelLabs/bayesian-torch: Bayesian-Torch 0.4.0
, 2023 <p>New feature: Quantization framework in Bayesian-Torch. Support Post Training Quantization of Bayesian deep neural networks, enables efficient INT8 inference on Intel platforms.</p> What's Changed <ul> <li>Add support for output
Michael Beale +5 more
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Refining a Bayesian network using a chain event graph [PDF]
, 2013 The search for a useful explanatory model based on a Bayesian Network (BN) now has a long and successful history. However, when the dependence structure between the variables of the problem is asymmetric then this cannot be captured by the BN.
Barclay, Lorna M. +2 more
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A multi-layered Bayesian network model for structured document retrieval [PDF]
, 2003 New standards in document representation, like for example SGML, XML, and MPEG-7, compel Information Retrieval to design and implement models and tools to index, retrieve and present documents according to the given document structure. The paper presents
Fabio Crestani +10 more
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