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Power sum kernels on symmetric groups
The power sum kernels are a family of stationary kernels on symmetric groups Sn. These kernels are bi-invariant: the action of Sn on itself from both sides does not change their... -
Non-asymptotic approximations of neural networks by Gaussian processes
The dataset is not explicitly described in the paper, but it is mentioned that the authors study the extent to which wide neural networks may be approximated by Gaussian processes. -
PEGP-VAE dataset
The dataset consists of 100 video sequences of a micro-particle in a 2-dimensional space. Each video sequence has a duration of 30 µs with one frame per µs. -
GP-Tree: A Gaussian Process Classifier for Few-Shot Incremental Learning
Gaussian processes (GPs) are non-parametric, flexible models that work well in many tasks. Combining GPs with deep learning methods via deep kernel learning (DKL) is especially... -
Gaussian Processes on Graphs via Spectral Kernel Learning
Gaussian Processes on Graphs via Spectral Kernel Learning -
Gaussian Control Barrier Function
The dataset used in this paper is a set of safety samples or observations to construct the Gaussian Control Barrier Function (GCBF) online.
