We introduce new modules in the open-source PyCBC gravitational-wave astronomy toolkit that implement Bayesian inference for compact-object binary mergers. We review the Bayesian inference methods ...

A research team at Tohoku University's Advanced Institute for Materials Research (WPI-AIMR) has developed a new technique to rapidly and accurately determine the charge state of electrons confined in ...

Dirichlet process (DP) priors are a popular choice for semiparametric Bayesian random effect models. The fact that the DP prior implies a non-zero mean for the random effect distribution creates an ...

Virtually all computations performed by the nervous system are subject to uncertainty and taking this into account is critical for making inferences about the outside world. For instance, imagine ...

Articulate the primary interpretations of probability theory and the role these interpretations play in Bayesian inference Use Bayesian inference to solve real-world statistics and data science ...