Metropolis–Hastings sampling of paths

Sampling diffusive transition paths.

The authors address the problem of sampling double-ended diffusive paths. The ensemble of paths is expressed using a symmetric version of the Onsager-Machlup formula, which only requires evaluation of the force field and which, upon direct time discretization, gives rise to a symmetric integrator that is accurate to second order. Efficiently sampling this ensemble requires avoiding the well-kno...

Metropolis-Hastings sampling of paths

We consider the previously unsolved problem of sampling cycle-free paths according to a given distribution from a general network. The problem is difficult because of the combinatorial number of alternatives, which prohibits a complete enumeration of all paths and hence also forbids to compute the normalizing constant of the sampling distribution. The problem is important because the ability to...

Title Sampling diffusive transition paths

Sampling social networks using shortest paths

In recent years, online social networks (OSN) have emerged as a platform of sharing variety of information about people, and their interests, activities, events and news from real worlds. Due to the large scale and access limitations (e.g., privacy policies) of online social network services such as Facebook and Twitter, it is difficult to access the whole public network in a limited amount of ...

Optimal Sampling In the Space of Paths: Preliminary Results

While spatial sampling has received much attention in recent years, our understanding of sampling issues in the function space of trajectories remains limited. This paper presents a structured approach to the selection of a finite control set, derived from the infinite function space of possible controls, which is optimal in some useful sense. We show from first principles that the degree to wh...