162 citations · 579 across the 17 of their papers we have counts for
3 papers · 1 filter
Kernel Sequential Monte Carlo
Ingmar Schuster, Heiko Strathmann, Brooks Paige +1
We propose kernel sequential Monte Carlo (KSMC), a framework for sampling from static target densities. KSMC is a family of sequential Monte Carlo algorithms that are based on buil…
Gradient-free Hamiltonian Monte Carlo with Efficient Kernel Exponential Families
Heiko Strathmann, Dino Sejdinovic, Samuel Livingstone +2
We propose Kernel Hamiltonian Monte Carlo (KMC), a gradient-free adaptive MCMC algorithm based on Hamiltonian Monte Carlo (HMC). On target densities where classical HMC is not an o…
Unbiased Bayes for Big Data: Paths of Partial Posteriors
Heiko Strathmann, Dino Sejdinovic, Mark Girolami
A key quantity of interest in Bayesian inference are expectations of functions with respect to a posterior distribution. Markov Chain Monte Carlo is a fundamental tool to consisten…