<p>The left panel shows the full model, and the right panel shows the same model expressed in compact form. Nodes denote random variables; observed random variables are shaded while latent random variables are not; edges denote possible dependences. The box in the right panel is called a <i>plate</i>; it denotes independent and identically distributed replicates.</p
<p>Plate Diagram for the simplified Bayesian multinomial logistic random effects model.</p
<p>Graphical representation of an asymmetrical five-state 2-parameter Markov chain model.</p
This report 1 presents probabilistic graphical models that are based on imprecise probabilities usin...
<p>A graphical model illustrates the dependencies between the variables of a model. The plates in th...
Probabilistic graphical models, such as Bayesian networks, allow representing conditional independen...
<p>Each node represents a variable. Edges represent probabilistic dependencies. Each node is associa...
<p>The more abstract a parameter, the higher it is in the graph. Deterministic variables have double...
<p>Shaded circles represent observed variables, and unshaded circles represent latent variables to b...
<p>A graphical model that describes the generation process of an ensemble PPI network with weighted ...
Graphical models are a flexible framework for building statistical models on large collections of ra...
<p>The graphical model is a Dynamic Bayesian Network [<a href="http://www.ploscompbiol.org/article/i...
<p>Nodes correspond to variables in the model and edges correspond to dependencies between variables...
The idea of graphical models is to use the language of graph theory to unify different classes of us...
<p>Boxes refer to variables in the model, where latent variables are represented by dotted line boxe...
<p>The distributions illustrated here have density bins of 1 wILI unit, which differs from those use...
<p>Plate Diagram for the simplified Bayesian multinomial logistic random effects model.</p
<p>Graphical representation of an asymmetrical five-state 2-parameter Markov chain model.</p
This report 1 presents probabilistic graphical models that are based on imprecise probabilities usin...
<p>A graphical model illustrates the dependencies between the variables of a model. The plates in th...
Probabilistic graphical models, such as Bayesian networks, allow representing conditional independen...
<p>Each node represents a variable. Edges represent probabilistic dependencies. Each node is associa...
<p>The more abstract a parameter, the higher it is in the graph. Deterministic variables have double...
<p>Shaded circles represent observed variables, and unshaded circles represent latent variables to b...
<p>A graphical model that describes the generation process of an ensemble PPI network with weighted ...
Graphical models are a flexible framework for building statistical models on large collections of ra...
<p>The graphical model is a Dynamic Bayesian Network [<a href="http://www.ploscompbiol.org/article/i...
<p>Nodes correspond to variables in the model and edges correspond to dependencies between variables...
The idea of graphical models is to use the language of graph theory to unify different classes of us...
<p>Boxes refer to variables in the model, where latent variables are represented by dotted line boxe...
<p>The distributions illustrated here have density bins of 1 wILI unit, which differs from those use...
<p>Plate Diagram for the simplified Bayesian multinomial logistic random effects model.</p
<p>Graphical representation of an asymmetrical five-state 2-parameter Markov chain model.</p
This report 1 presents probabilistic graphical models that are based on imprecise probabilities usin...