A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf
.
Bridging the gap between theory and practice of approximate Bayesian inference
2013
Cognitive Systems Research
Iris van Rooij (i.vanrooij@donders.ru.nl) Abstract In computational cognitive science, many cognitive processes seem to be successfully modeled as Bayesian computations. Yet, many such Bayesian computations has been proven to be computationally intractable (NP-hard) for unconstrained input domains, even if only an approximate solution is sought. This computational complexity result seems to be in strong contrast with the ease and speed with which humans can typically make the inferences that
doi:10.1016/j.cogsys.2012.12.008
fatcat:jauxp3azprc5xgol4c6ba3h2xq