This a Bayesian ICA algorithm for the linear instantaneous mixing model with additive Gaussian noise [1]. The inference problem is solved by ML-II, i.e. the sources are found by integration over the source posterior and the noise covariance and mixin

Bayesian Inference of Signaling Network Topology in a Cancer Cell Line-To shed light on signaling network topology in specic contexts, such as cancer, requires interrogation of multiple proteins through time and statistical approaches to make

An implementation of forward–backward algorithm. This algorithm is an inference algorithm for hidden Markov models which computes the posterior marginals of all hidden state variables given a sequence of observations/emissions.