An observer desires to record a realization of a stationary two-state Markov chain X, but experimental conditions are such that he instead sees a realization of an ...

We consider the application of Markov chain Monte Carlo (MCMC) estimation methods to random-effects models and in particular the family of discrete time survival models. Survival models can be used in ...

The ability to deal with unseen objects in a zero-shot manner makes machine learning models very attractive for applications in robotics, allowing robots to enter previously unseen environments and ...