971 citations · 3k across the 74 of their papers we have counts for
3 papers · 2 filters
Spatial Mapping with Gaussian Processes and Nonstationary Fourier Features
Jean-Francois Ton, Seth Flaxman, Dino Sejdinovic +1
The use of covariance kernels is ubiquitous in the field of spatial statistics. Kernels allow data to be mapped into high-dimensional feature spaces and can thus extend simple line…
Bayesian Approaches to Distribution Regression
Ho Chung Leon Law, Danica J. Sutherland, Dino Sejdinovic +1
Distribution regression has recently attracted much interest as a generic solution to the problem of supervised learning where labels are available at the group level, rather than…
Testing and Learning on Distributions with Symmetric Noise Invariance
Ho Chung Leon Law, Christopher Yau, Dino Sejdinovic
Kernel embeddings of distributions and the Maximum Mean Discrepancy (MMD), the resulting distance between distributions, are useful tools for fully nonparametric two-sample testing…