Bayesian inference networks and spreading activation in hypertext systems

The ill-posed nature of missing variable models offers a challenging testing ground for new computational techniques. This is the case for the mean-field variational Bayesian inference. The behavior of this approach in the setting of the Bayesian probit ...

The original Bayes used an analogy involving an invariant prior and a statistical model and argued that the resulting combination of prior with likelihood provided a probability description of an unknown parameter value in an application; the ...

There is growing evidence from psychophysical and neurophysiological studies that the brain utilizes Bayesian principles for inference and decision making. An important open question is how Bayesian inference for arbitrary graphical models can be ...