DNest4: Diffusive Nested Sampling in C++ and Python

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...

Title Sampling diffusive transition paths

Slice sampling in nested IBP

We develop a nonparametric Bayesian method that explores the infinite space of latent features and finds the best subset in the sense of posterior probability. When the data appear in several groups, there should be different measures reflecting the differences between the groups. We formalize this as a nested Indian buffet process (nIBP) by assuming different measures according to the specific...

Nested sampling with demons

This article looks at Skilling’s nested sampling from a physical perspective and interprets it as a microcanonical demon algorithm. Using key quantities of statistical physics we investigate the performance of nested sampling on complex systems such as Ising, Potts and protein models. We show that releasing multiple demons helps to smooth the truncated prior and eases sampling from it because t...

Quality Control in Diffusive Sampling Networks

The urban centres are growing extremely quickly throughout Latin America and, as a consequence air pollution is also growing due to increasing traffic. The Clean Air Programme, financed by the Swiss Agency for Development and Cooperation (SDC), was carried out by the Swiss Foundation for Technical Cooperation (Swisscontact) was carried out in 6 Central American cities [1]. The project's goal wa...