2.2k citations · 4k across the 42 of their papers we have counts for
3 papers · 1 filter
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…
Detecting causal associations in large nonlinear time series datasets
Jakob Runge, Peer Nowack, Marlene Kretschmer +2
Identifying causal relationships from observational time series data is a key problem in disciplines such as climate science or neuroscience, where experiments are often not possib…