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Questions tagged [bayesian-networks]

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

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4 votes
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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 ...
Jake's user avatar
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3 votes
1 answer
157 views

How are the "Link Strength true", "Link Strength blind" and "Mutual Information" calculated in this report on Bayesian networks?

I'm trying to understand how to calculate the strength of every arc in a Bayesian Network. I came across this report Measuring Connection Strengths and Link Strengths in Discrete Bayesian Networks, ...
qillbel's user avatar
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2 votes
0 answers
31 views

What are the practical problems where full bayesian treatment is affordable?

Suppose, I have a problem, where there is rather a small number of training samples, and transfer learning from ImageNet or some huge NLP dataset is not relevant for this task. Due to the small number ...
spiridon_the_sun_rotator's user avatar
2 votes
1 answer
78 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 ...
Hongmin Yang's user avatar
2 votes
0 answers
26 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 ...
Shashank Gupta's user avatar
1 vote
0 answers
74 views

Calculation of the CPTs in a Dynamic Bayesian Network

I am trying to figure out how to build my DBN (with pyAgrum), and I am a bit confused. Let us say I have the network on the next figure. I am interested in the variable $B$. At each time $t$, I am ...
Dark Patate's user avatar
1 vote
0 answers
13 views

variational inference but with a weighted loglikelihood

I would like to know if it's correct if I substitute in the ELBO formula a weighted sum of the loglikelihood $$\sum E_{q_{\theta}(w)}[w_i \ln{p(y_i|f^{w}(x_i))}]$$ in place of the traditional sum. ...
Alucard's user avatar
  • 111
1 vote
0 answers
18 views

In the original GAN paper, why is it mentioned that you can sample deep directed graphical models without a Markov chain?

In the original GAN paper (table 2), why is it mentioned that you can sample deep directed graphical models without a Markov chain (well, they say without difficulties, but others list MCMC as a ...
beelze-b's user avatar
1 vote
0 answers
79 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 ...
Gooby's user avatar
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1 vote
1 answer
64 views

How to perform structure learning for Bayesian network given already partially constructed Bayesian network?

Let's assume that we have a dataset of variables (random events)I apriori would like to set dependency conditions between some of them and perform structure learning to figure out the rest of the ...
Sultan1991's user avatar
1 vote
2 answers
270 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 ...
Atena's user avatar
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What model is good for learning both within and across categories?

How can I incorporate both general trends and subcategory-specific trends into a model? Let's say I am predicting factors that affect import volume, for example. There are many industries which have ...
BigMistake's user avatar
0 votes
0 answers
16 views

Requesting resources on causal networks for 2D strategy game

I am requesting research, articles, abstracts or interesting opinions that will help me create a complex causal neural network. There are many detailed resources on causal discovery, image recognition,...
Mitsuformation's user avatar
0 votes
1 answer
71 views

Why are Directed Graphical Models considered ML methods?

Consider the following problem. The probability of being born in countries [1,2,3,4] is given by [a, b, c, d] respectively. This is a categorical problem. Now, assume that the height of a person ...
user1029384756's user avatar
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0 answers
55 views

What makes Sequential Bayesian Filtering and Smoothing tractable?

I'm currently diving into the Bayesian world and I find it pretty fascinating. I've so far understood that applying the Bayes' Rule, i.e. $$\text{posterior} = \frac{\text{likelihood}\times \text{prior}...
igorTh2's user avatar
-1 votes
1 answer
93 views

Given A and B, C are independent of each other. Given A, B and C, D and E are independent of each other. What is the minimal number of parameters?

Assuming all variables $A, B, C, D,$ and $E$ are random binary variables. I come up with Bayes net: $D \rightarrow B \rightarrow A \leftarrow C \leftarrow E$ which has the minimal number of parameters ...
BOB's user avatar
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