130 citations · 297 across the 22 of their papers we have counts for
Showing 2023 · stat.MLShow all
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stat.ML2023★ 1 cited
Leveraging Locality and Robustness to Achieve Massively Scalable Gaussian Process Regression
Robert Allison, Anthony Stephenson, Samuel F +1
The accurate predictions and principled uncertainty measures provided by GP regression incur O(n^3) cost which is prohibitive for modern-day large-scale applications. This has moti…
stat.ML2023
Provably Reliable Large-Scale Sampling from Gaussian Processes
Anthony Stephenson, Robert Allison, Edward Pyzer-Knapp
When comparing approximate Gaussian process (GP) models, it can be helpful to be able to generate data from any GP. If we are interested in how approximate methods perform at scale…