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Differentiating between Bayesian parameter learning and structure learning based on behavioural and pupil measures [PDF]

PLoS ONE, 2023
Within predictive processing two kinds of learning can be distinguished: parameter learning and structure learning. In Bayesian parameter learning, parameters under a specific generative model are continuously being updated in light of new evidence ...
Danaja Rutar, Olympia Colizoli, Luc Selen, Lukas Spieß, Johan Kwisthout, Sabine Hunnius   +5 more
doaj   +3 more sources

Bilevel Parameter Learning for Higher-Order Total Variation Regularisation Models. [PDF]

J Math Imaging Vis, 2017
We consider a bilevel optimisation approach for parameter learning in higher-order total variation image reconstruction models. Apart from the least squares cost functional, naturally used in bilevel learning, we propose and analyse an alternative cost ...
De Los Reyes JC, Schönlieb CB, Valkonen T.   +2 more
europepmc   +4 more sources

A guide to bayesian networks software for structure and parameter learning, with a focus on causal discovery tools [PDF]

Frontiers in Systems Biology
A representation of the cause-effect mechanism is needed to enable artificial intelligence to represent how the world works. Bayesian Networks (BNs) have proven to be an effective and versatile tool for this task.
Francesco Canonaco, Francesco Canonaco, Joverlyn Gaudillo, Nicole Astrologo, Fabio Stella, Enzo Acerbi   +5 more
doaj   +2 more sources

A parameter-free learning automaton scheme

Frontiers in Neurorobotics, 2022
For a learning automaton, a proper configuration of the learning parameters is crucial. To ensure stable and reliable performance in stochastic environments, manual parameter tuning is necessary for existing LA schemes, but the tuning procedure is time ...
Xudie Ren, Shenghong Li, Hao Ge
doaj   +3 more sources

Correction: A guide to bayesian networks software for structure and parameter learning, with a focus on causal discovery tools [PDF]

Frontiers in Systems Biology
Francesco Canonaco, Francesco Canonaco, Joverlyn Gaudillo, Nicole Astrologo, Fabio Stella, Enzo Acerbi   +5 more
doaj   +2 more sources

The M-DUCG Methodology to Calculate the Joint Probability Distribution of Directed Cycle Graph With Local Data and Domain Causal Knowledge

IEEE Access, 2021
Modeling a complex system with a large number of variables at one time and collecting global data on a large scale is usually not practical. It is ideal to model the global system according to only local data and structures, and then synthesize them ...
Kun Qiu, Qin Zhang
doaj   +1 more source

Bearing Fault Diagnosis Under Small Data Set Condition: A Bayesian Network Method With Transfer Learning for Parameter Estimation

IEEE Access, 2022
Bearings are broadly applied in various types of industrial systems. Fault diagnosis, as a promising way for reliability of modern industrial internet of thing applications, has attracted increasing attention from both academia and industry fields. Being
Yongyan Hou, Ao Yang, Wenqiang Guo, Enrang Zheng, Qinkun Xiao, Zhigao Guo, Zixuan Huang   +6 more
doaj   +1 more source

Bayesian network parameter learning algorithm based on improved QMAP

Xibei Gongye Daxue Xuebao, 2021
Small data sets make the statistical information in Bayesian network parameter learning inaccurate, which makes it difficult to get accurate Bayesian network parameters based on data.
Di Ruohai, Li Ye, Wan Kaifang, Lyu Zhigang, Wang Peng   +4 more
doaj   +1 more source

Study on cause of coal and gas outburst accident based on D-S evidence theory and Bayesian network

Meikuang Anquan, 2023
To explore the mechanism and influencing factors of coal and gas outburst accidents in coal mines, the factors inducing coal and gas outburst accidents were selected from four aspects: human, machine, environment and management, and the risk of accidents
QIN Yan, SHENG Wu
doaj   +1 more source

The Situation Assessment of UAVs Based on an Improved Whale Optimization Bayesian Network Parameter-Learning Algorithm

Drones, 2023
To realize unmanned aerial vehicle (UAV) situation assessment, a Bayesian network (BN) for situation assessment is established. Aimed at the problem that the parameters of the BN are difficult to obtain, an improved whale optimization algorithm based on ...
Weinan Li, Weiguo Zhang, Baoning Liu, Yicong Guo   +3 more
doaj   +1 more source