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Some comments here:

> Main article: Bayesian Networks

Dead link

> Followed by the chain rule and using independences we have,

Probability page doesn't introduce the chain rule.

> The following is an example encoding of this probabilistic model as a CNF.

The latex expressions are hard to read. Put some space between expressions?

> Weight of the positive literal λ θ x | u {\displaystyle \lambda _{\theta _{x|u}}} {\displaystyle \lambda _{\theta _{x|u}}} is P r θ x | u {\displaystyle Pr_{\theta _{x|u}}} {\displaystyle Pr_{\theta _{x|u}}}

I don't see this literal appear anywhere. I think you meant \theta _{x|u}

> The weights for the literals define a weight for each model w {\displaystyle w} {\displaystyle w} as follows.

What is a model?

> For each parameter P r ( x i | u 1 , u 2 , . . . , u n ) {\displaystyle Pr(x_{i}|u_{1},u_{2},...,u_{n})} {\displaystyle Pr(x_{i}|u_{1},u_{2},...,u_{n})}we generate the following clauses,

What are the variables u_1, ..., u_n? (for ENC1 and ENC2)

> Main article: Knowledge Compilation

Dead link.

> Model counting and arithmetic circuit

"Smooth d-DNNF" and "Model counting and arithmetc circuit" need some plain explanations.

> The irrelevant variables are defined as the variables that their value does not affect the probability (that is uniform over literals).

the variables that their value => the variable whose values. What probability?

> Decomposability

I think the scope gets too large all of a sudden here. ENC1 and ENC2 were pretty coherent.

"Dead link."

The template or macro

link format was not compatible with the pages,

It seems that it is fixed, I added "Course:CPSC522/" and it fixed the problem but it still doesn't look good.

"Probability page doesn't introduce the chain rule."

I think I mistook with the Wikipedia page, Bayesian_Networks also uses the same link for chain-rule, I linked it to Bayesian_Networks for now.

"The latex expressions are hard to read. Put some space between expressions?"

I centralized most of the main formulas for more readability and added \qquad before some of the clauses.

"I don't see this literal appear anywhere. I think you meant \theta _{x|u}"

That was a mistake changed to \theta_x|u and Pr(x|u). (This instance corrected)

"What is a model?"

Unfortunately, there are two different concepts. A probabilistic model(e.g. similar to graphical models) and an assignment to the variables both are called a model. Both are mentioned in the initial paragraph. I added another sentence for further clarification.

"What are the variables u_1, ..., u_n? (for ENC1 and ENC2)"

I think this was Ok, but I added a sentence in ENC1.

"'Smooth d-DNNF' and 'Model counting and arithmetic circuit' need some plain explanations."

There is a main page which is referenced. I just briefly explained d-DNNF and I don't know much more about arithmetic circuits.

"the variables that their value => the variable whose values. What probability?"

whose value sounds right,(that is (added: their weight is) uniform over literals)

"I think the scope gets too large all of a sudden here. ENC1 and ENC2 were pretty coherent."

I think taking advantage of these structures were important. Though it was beyond the available time. added:(that is the factor value in the CPT is uniform over literals of that variable)