2.6k citations · 11.1k across the 96 of their papers we have counts for
14 papers · 1 filter
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…
Sublinear-Time Approximate MCMC Transitions for Probabilistic Programs
Yutian Chen, Vikash Mansinghka, Zoubin Ghahramani
Probabilistic programming languages can simplify the development of machine learning techniques, but only if inference is sufficiently scalable. Unfortunately, Bayesian parameter e…
Warped Mixtures for Nonparametric Cluster Shapes
Tomoharu Iwata, David Duvenaud, Zoubin Ghahramani
A mixture of Gaussians fit to a single curved or heavy-tailed cluster will report that the data contains many clusters. To produce more appropriate clusterings, we introduce a mode…
Beta diffusion trees and hierarchical feature allocations
Creighton Heaukulani, David A. Knowles, Zoubin Ghahramani
We define the beta diffusion tree, a random tree structure with a set of leaves that defines a collection of overlapping subsets of objects, known as a feature allocation. A genera…
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…
Predictive Entropy Search for Efficient Global Optimization of Black-box Functions
José Miguel Hernández-Lobato, Matthew W. Hoffman, Zoubin Ghahramani
We propose a novel information-theoretic approach for Bayesian optimization called Predictive Entropy Search (PES). At each iteration, PES selects the next evaluation point that ma…