47 citations · 49 across the 3 of their papers we have counts for
3 papers
stat.ML2023★ 1 cited
Mixtures of Gaussian process experts based on kernel stick-breaking processes
Yuji Saikai, Khue-Dung Dang
Mixtures of Gaussian process experts is a class of models that can simultaneously address two of the key limitations inherent in standard Gaussian processes: scalability and predic…
cs.LG2023★ 47 cited
Deep reinforcement learning for irrigation scheduling using high-dimensional sensor feedback
Yuji Saikai, Allan Peake, Karine Chenu
Deep reinforcement learning has considerable potential to improve irrigation scheduling in many cropping systems by applying adaptive amounts of water based on various measurements…
cs.LG2022★ 1 cited
The case for fully Bayesian optimisation in small-sample trials
Yuji Saikai
While sample efficiency is the main motive for use of Bayesian optimisation when black-box functions are expensive to evaluate, the standard approach based on type II maximum likel…