NEO: Non Equilibrium Sampling on the Orbit of a Deterministic Transform

Understand

Sampling from a complex distribution $\pi$ and approximating its intractable normalizing constant Z are challenging problems.

• In this paper, a novel family of importance samplers (IS) and Markov chain Monte Carlo (MCMC) samplers is derived.
• Given an invertible map T, these schemes combine (with weights) elements from the forward and backward Orbits through points sampled from a proposal distribution $\rho$.
• The map T does not leave the target $\pi$ invariant, hence the name NEO, standing for Non-Equilibrium Orbits.