42 citations · 53 across the 4 of their papers we have counts for
4 papers
Neural Non-Stationary Spectral Kernel
Sami Remes, Markus Heinonen, Samuel Kaski
Standard kernels such as Matérn or RBF kernels only encode simple monotonic dependencies within the input space. Spectral mixture kernels have been proposed as general-purpose, fle…
Non-Stationary Spectral Kernels
Sami Remes, Markus Heinonen, Samuel Kaski
We propose non-stationary spectral kernels for Gaussian process regression. We propose to model the spectral density of a non-stationary kernel function as a mixture of input-depen…
A Mutually-Dependent Hadamard Kernel for Modelling Latent Variable Couplings
Sami Remes, Markus Heinonen, Samuel Kaski
We introduce a novel kernel that models input-dependent couplings across multiple latent processes. The pairwise joint kernel measures covariance along inputs and across different…
Classification of weak multi-view signals by sharing factors in a mixture of Bayesian group factor analyzers
Sami Remes, Tommi Mononen, Samuel Kaski
We propose a novel classification model for weak signal data, building upon a recent model for Bayesian multi-view learning, Group Factor Analysis (GFA). Instead of assuming all da…