6 citations · 10 across the 2 of their papers we have counts for
2 papers
cs.LG2020★ 4 cited
Equivariant Learning of Stochastic Fields: Gaussian Processes and Steerable Conditional Neural Processes
Peter Holderrieth, Michael Hutchinson, Yee Whye Teh
Motivated by objects such as electric fields or fluid streams, we study the problem of learning stochastic fields, i.e. stochastic processes whose samples are fields like those occ…
math.ST2019★ 6 cited
Cores for Piecewise-Deterministic Markov Processes used in Markov Chain Monte Carlo
Peter Holderrieth
We show fundamental properties of the Markov semigroup of recently proposed MCMC algorithms based on Piecewise-deterministic Markov processes (PDMPs) such as the Bouncy Particle Sa…