48 citations · 141 across the 14 of their papers we have counts for
4 papers · 1 filter
Sparse Gaussian Process Hyperparameters: Optimize or Integrate?
Vidhi Lalchand, Wessel P. Bruinsma, David R. Burt +1
The kernel function and its hyperparameters are the central model selection choice in a Gaussian proces (Rasmussen and Williams, 2006). Typically, the hyperparameters of the kernel…
Numerically Stable Sparse Gaussian Processes via Minimum Separation using Cover Trees
Alexander Terenin, David R. Burt, Artem Artemev +4
Gaussian processes are frequently deployed as part of larger machine learning and decision-making systems, for instance in geospatial modeling, Bayesian optimization, or in latent…
A Note on the Chernoff Bound for Random Variables in the Unit Interval
Andrew Y. K. Foong, Wessel P. Bruinsma, David R. Burt
The Chernoff bound is a well-known tool for obtaining a high probability bound on the expectation of a Bernoulli random variable in terms of its sample average. This bound is commo…
Wide Mean-Field Bayesian Neural Networks Ignore the Data
Beau Coker, Wessel P. Bruinsma, David R. Burt +2
Bayesian neural networks (BNNs) combine the expressive power of deep learning with the advantages of Bayesian formalism. In recent years, the analysis of wide, deep BNNs has provid…