Questions tagged [bayesian-network]

For questions related to Bayesian networks, which are e.g. used to study causality (or causation) in AI.

11 questions with no upvoted or accepted answers
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What are the main benefits of using Bayesian networks?

I have some trouble understanding the benefits of Bayesian networks. Am I correct that the key benefit of the network is that one does not need to use chain rule of probability in order to calculate ...
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229 views

How can I draw a Bayesian network for this problem with birds?

I am working on the following problem to gain an understanding of Bayesian networks and I need help drawing it: Birds frequently appear in the tree outside of your window in the morning and ...
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45 views

Why do Bayesian algorithms work well with small datasets?

I read very often that Bayesian algorithms work well on small datasets. Why is that? I think it is because they might generalize more, but why is that? See also Investigating the use of Bayesian ...
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19 views

In Probabilistic Graphical Model (written by Daphne Koller), what's the meaning of “parameter” in representation of the distribution?

I just started to read the PGM book written by Daphne Koller. In the chapter of Bayesian Network Representation(Chapter 3), there are some descriptions about the standard parameterization of the joint ...
2
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1answer
73 views

Mutual Information and Link Strength in Bayesian Network

I'm trying to understand how to calculate the strength of every arc in Bayesian Network. I came across this paper, https://smartech.gatech.edu/bitstream/handle/1853/14331/GT-IIC-07-01.pdf?sequence=1&...
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25 views

Deriving hyperparameter updates in Online Interactive Collaborative Filtering

I've been going through "Online Interactive Collaborative Filtering Using Multi-Armed Bandit with Dependent Arms" by Wang et al. and am unable to understand how the update equations for the ...
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44 views

What is the point of converting conditional probability to factor for Variable Elimination?

I have this slide from my AI class on using a Bayes network to compute a conditional probability. I don't really understand the point of converting the conditional probabilities to factors (besides ...
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2answers
92 views

Can maximum likelihood be used as a classifier?

I am confused in understanding the maximum likelihood as a classifier. I know what is Bayesian network and I know that ML is used for estimating the parameters of models. Also, I read that there are ...
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20 views

Does the measurement noise refers to the variance in the predicted or observed measurements in Kalman filters?

In the Kalman filter we have s.th. called the process noise and the measurement noise. A measurement is computed by multiplying our state $x$ with a matrix $H$ and adding the measurement noise $r$. ...
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17 views

Kalman Filter: Intuitive explanation of gain and variability in measurements and estimated states?

I'm trying to understand how Bayesian Filters (especially Kalman Filter) works. My understanding so far (please correct me if I am wrong) Assume I have measurements $y_k$, states $x_k$, the estimated ...
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1answer
33 views

Does the Bayesian MAP give a probability distribution over unseen t*?

I'm working my way through the Bayesian world. So far i've understood that the MLE or the MPA are point estimates, therefore using such models just output one specific value and not an distribution. ...