In this paper, we tackle the problem of simulating from the posterior distribution over paths in these models, given partial and noisy observations; this typically cannot be performed analytically.Expand

We introduce a kernelized Stein discrepancy measure for discrete spaces, and develop a nonparametric goodness-of-fit test for discrete distributions with intractable normalization constants.Expand

We propose a simple and general framework to construct dependent DPs by marginalizing and normalizing a single gamma process over an extended space such that neighbouring DPs are more dependent.Expand

In this paper, we describe a nonparametric Bayesian approach where a renewal process is modulated by a random intensity function which is given a Gaussian process prior.Expand

We propose a novel Markov chain Monte Carlo sampling method for Markov jump processes and continuous-time Bayesian networks that avoids the need for such expensive computations.Expand

In this paper we propose two constructions of dependent normalized random measures, a class of nonparametric priors over dependent probability measures.Expand