Examples of using Bayesian in English and their translations into Ukrainian
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Bayesian algorithms and methods.
It's called Bayesian inference.
Bayesian statistical analysis.
First applications in the design of schedule, Bayesian networks;
Bayesian network Deep learning Hinton G(2009).
People also translate
Which takes us to the other forgotten terms in Bayesian inference.
The adjective Bayesian itself dates to the 1950s;
A HMM can be considered the simplest dynamic Bayesian network.
Suboptimal Bayesian strategies for recognition and learning.
Evaluating it correctly is the key to Bayesian model comparison.
Bayesian spam filtering is a common example of supervised learning.
Gamalon uses the technique of Bayesian programming, program synthesis.
Bayesian statistics is often used for inferring latent variables.
(2003) explain how to use sampling methods for Bayesian linear regression.
The purpose of Bayesian spam filtering is to eliminate junk e-mails.
Efficient algorithms exist that perform inference and learning in Bayesian networks.
Bayesian programming is a formal and concrete implementation of this"robot".
Gaussian processes are part of the family of analyses used by Bayesian methods.
Bayesian reading list, categorized and annotated by Tom Griffiths.
The Kalman filter canbe presented as one of the simplest dynamic Bayesian networks.
The Bayesian design of experiments includes a concept called'influence of prior beliefs'.
Overview of methods of reverse engineering of gene regulatory networks: Boolean and Bayesian networks.
He makes a decision based on Bayesian reasoning to determine the most rational choice.
The Kalman filter can be considered to be one of the most simple dynamic Bayesian networks.
The Bayesian probability is used to refine predictions about the world using experience.
When you received their response, you implicitly did a Bayesian updating on those probabilities.
For example, a Bayesian network could represent the probabilistic relationships between diseases and symptoms.
The following models use belief propagation or belief revision in singly connected Bayesian networks.
Several methods of Bayesian estimation select measurements of central tendency from the posterior distribution.
Tarasov Computer methods of disease diagnosis based on Bayesian recognition procedures.