Abstract. Bayesian nets (BNs) appeared in the 1980s as a solution to computational and representational problems encountered in knowledge representation of uncertain information. S...
We present an algorithm name cSAT+ for learning the causal structure in a domain from datasets measuring different variable sets. The algorithm outputs a graph with edges correspo...
Sofia Triantafilou, Ioannis Tsamardinos, Ioannis G...
Bayesian networks can be used to extract explanations about the observed state of a subset of variables. In this paper, we explicate the desiderata of an explanation and confront ...
: This paper presents a causal simulation method for incompletely known dynamic systems in process engineering. The causal model of a process is represented as both a causal networ...
Discovering causal relations among observed variables in a given data set is a main topic in studies of statistics and artificial intelligence. Recently, some techniques to disco...