# Tagged Questions

The tag has no usage guidance.

31 views

### Comparative study between Deep neural nets and Bayesian Networks

Is there any comparative study that showcases the powers of Bayesian Networks and Deep learning in their respective favorable setup and how they compare? I tried to go through blogs but couldn't find ...
12 views

### Does marginalizing on a Bayesian network preserve its original independence assumptions?

I know that marginalizing over a Bayesian network causes changes to the graph (e.g. marginalizing node c in the V-structure given by $a \rightarrow c \leftarrow b$ results in $a$ and $b$ being ...
23 views

### Variable elimination in Bayesian network

I'm trying to check if my understanding of variable elimination is correct. Assume the above Bayesian network is factorized as: $p(a,b,d,e,l,s,t,x) = p(a)p(t|a)p(e|t,l)p(x|e)p(l|s)p(b|s)p(d|b,e)p(s)$...
22 views

### About the complexity of learning probabilistic graphical models

I guess that one way of measuring the complexity of learning a joint probability distribution is as its "sample complexity" (which is also sometimes known as its "distributional learning complexity"?) ...
25 views

### Have people looked at “Hypergraphical” models?

Graphical models are a very useful tool with many applications, whereby a joint distribution of a set of random variables is modeled using only pairwise dependencies between the variables, and two ...
77 views

### Difference between Bayesian Networks and Dynamic Bayesian Networks

I'm studying Bayesian networks and want to clarify a couple of things with people who are more knowledgable in the area than me. As far as I understand it, a Bayesian network (BN) is a directed ...
249 views

### Maximum likelihood estimate for softmax function

Given an undirected graphical model with no edges and only N nodes, I am trying to find a closed form solution to the ML estimate of each node given that \$p(x|\theta)=\frac{\exp(\sum_{s\in V}\...