1 citations · 2 across the 6 of their papers we have counts for
Showing stat.COShow all
2 papers · 1 filter
stat.CO2021
On MCMC for variationally sparse Gaussian processes: A pseudo-marginal approach
Karla Monterrubio-Gómez, Sara Wade
Gaussian processes (GPs) are frequently used in machine learning and statistics to construct powerful models. However, when employing GPs in practice, important considerations must…
stat.CO2018
Posterior Inference for Sparse Hierarchical Non-stationary Models
Karla Monterrubio-Gómez, Lassi Roininen, Sara Wade +2
Gaussian processes are valuable tools for non-parametric modelling, where typically an assumption of stationarity is employed. While removing this assumption can improve prediction…