Bayesian networks are mathematically and statistically rigorous techniques for handling uncertainty. The field of forensic science has recently attributed increased attention to the many advantages of this graphical method for assisting the evaluation of scientific evidence. However, the majority of contributions that relate to this topic restrict themselves to the presentation of already \u201cconstructed\u201d BNs, and often, only a few explanations are given as to how one obtain a specific BN structure for a given problem. Based on several examples, the present paper will therefore attempt to explain in more detail some guiding considerations that might be helpful for the elicitation of appropriate structures for BNs
Bayesian networks (BN) have recently experienced increased interest and diverse applications in nume...
Errors in reasoning about probabilistic evidence can have severe consequences. In the legal domain a...
Bayesian networks are graphical models that have been developed in the field of artificial intellige...
The hierarchy of propositions has been accepted amongst the forensic science community for some time...
As a thorough aggregation of probability and graph theory, Bayesian networks currently enjoy widespr...
As a thorough aggregation of probability and graph theory, Bayesian networks currently enjoy widespr...
Solving forensic identification problems frequently requires complex probabilistic argument and comp...
Continuing developments in science and technology mean that the amounts of information forensic scie...
Continuing developments in science and technology mean that the amounts of information forensic scie...
Almost 30 years ago, Bayesian networks (BNs) were developed in the field of artificial intelligence ...
Continuing developments in science and technology mean that the amounts of information forensic scie...
Forensic scientists deal with the evaluation of a link between recovered ma- terial of unknown sourc...
The analysis of nominal data is often reduced to accumulation and description. Bayesian methods offe...
Computer (digital) forensic examiners typically write a report to document the examination process, ...
Bayesian networks (BN) have recently experienced increased interest and diverse applications in nume...
Errors in reasoning about probabilistic evidence can have severe consequences. In the legal domain a...
Bayesian networks are graphical models that have been developed in the field of artificial intellige...
The hierarchy of propositions has been accepted amongst the forensic science community for some time...
As a thorough aggregation of probability and graph theory, Bayesian networks currently enjoy widespr...
As a thorough aggregation of probability and graph theory, Bayesian networks currently enjoy widespr...
Solving forensic identification problems frequently requires complex probabilistic argument and comp...
Continuing developments in science and technology mean that the amounts of information forensic scie...
Continuing developments in science and technology mean that the amounts of information forensic scie...
Almost 30 years ago, Bayesian networks (BNs) were developed in the field of artificial intelligence ...
Continuing developments in science and technology mean that the amounts of information forensic scie...
Forensic scientists deal with the evaluation of a link between recovered ma- terial of unknown sourc...
The analysis of nominal data is often reduced to accumulation and description. Bayesian methods offe...
Computer (digital) forensic examiners typically write a report to document the examination process, ...
Bayesian networks (BN) have recently experienced increased interest and diverse applications in nume...
Errors in reasoning about probabilistic evidence can have severe consequences. In the legal domain a...
Bayesian networks are graphical models that have been developed in the field of artificial intellige...