140 citations · 735 across the 46 of their papers we have counts for
4 papers · 1 filter
Hamiltonian Monte Carlo for Probabilistic Programs with Discontinuities
Bradley Gram-Hansen, Yuan Zhou, Tobias Kohn +3
Hamiltonian Monte Carlo (HMC) is arguably the dominant statistical inference algorithm used in most popular "first-order differentiable" Probabilistic Programming Languages (PPLs).…
On the Pitfalls of Nested Monte Carlo
Tom Rainforth, Robert Cornish, Hongseok Yang +1
There is an increasing interest in estimating expectations outside of the classical inference framework, such as for models expressed as probabilistic programs. Many of these conte…
Interacting Particle Markov Chain Monte Carlo
Tom Rainforth, Christian A. Naesseth, Fredrik Lindsten +4
We introduce interacting particle Markov chain Monte Carlo (iPMCMC), a PMCMC method based on an interacting pool of standard and conditional sequential Monte Carlo samplers. Like r…
Asynchronous Anytime Sequential Monte Carlo
Brooks Paige, Frank Wood, Arnaud Doucet +1
We introduce a new sequential Monte Carlo algorithm we call the particle cascade. The particle cascade is an asynchronous, anytime alternative to traditional particle filtering alg…