most citedStatistical Inference for Generative Models with Maximum Mean Discrepancy

36 citations · 41 across the 3 of their papers we have counts for

collaborators

5 papers

stat.ME201936 cited

Statistical Inference for Generative Models with Maximum Mean Discrepancy

Francois-Xavier Briol, Alessandro Barp, Andrew B. Duncan +1

While likelihood-based inference and its variants provide a statistically efficient and widely applicable approach to parametric inference, their application to models involving in…

stat.CO2019

Stein Point Markov Chain Monte Carlo

Wilson Ye Chen, Alessandro Barp, François-Xavier Briol +4

An important task in machine learning and statistics is the approximation of a probability measure by an empirical measure supported on a discrete point set. Stein Points are a cla…

stat.CO20195 cited

Hamiltonian Monte Carlo on Symmetric and Homogeneous Spaces via Symplectic Reduction

Alessandro Barp, Anthony Kennedy, Mark Girolami

The Hamiltonian Monte Carlo method generates samples by introducing a mechanical system that explores the target density. For distributions on manifolds it is not always simple to…

math.ST2019

Irreversible Langevin MCMC on Lie Groups

Alexis Arnaudon, Alessandro Barp, So Takao

It is well-known that irreversible MCMC algorithms converge faster to their stationary distributions than reversible ones. Using the special geometric structure of Lie groups $\mat…

math.DG2019

Hamiltonian Monte Carlo On Lie Groups and Constrained Mechanics on Homogeneous Manifolds

Alessandro Barp

In this paper we show that the Hamiltonian Monte Carlo method for compact Lie groups constructed in \cite{kennedy88b} using a symplectic structure can be recovered from canonical g…