346 citations · 660 across the 4 of their papers we have counts for
4 papers · 1 filter
Score-Based Diffusion meets Annealed Importance Sampling
Arnaud Doucet, Will Grathwohl, Alexander G. D. G. Matthews +1
More than twenty years after its introduction, Annealed Importance Sampling (AIS) remains one of the most effective methods for marginal likelihood estimation. It relies on a seque…
GPflow: A Gaussian process library using TensorFlow
Alexander G. de G. Matthews, Mark van der Wilk, Tom Nickson +5
GPflow is a Gaussian process library that uses TensorFlow for its core computations and Python for its front end. The distinguishing features of GPflow are that it uses variational…
Scalable Variational Gaussian Process Classification
James Hensman, Alex Matthews, Zoubin Ghahramani
Gaussian process classification is a popular method with a number of appealing properties. We show how to scale the model within a variational inducing point framework, outperformi…
Classification using log Gaussian Cox processes
Alexander G. de. G Matthews, Zoubin Ghahramani
McCullagh and Yang (2006) suggest a family of classification algorithms based on Cox processes. We further investigate the log Gaussian variant which has a number of appealing prop…