1 citations · 2 across the 3 of their papers we have counts for
3 papers
stat.ML2021★ 1 cited
Scalable Multi-Task Gaussian Processes with Neural Embedding of Coregionalization
Haitao Liu, Jiaqi Ding, Xinyu Xie +3
Multi-task regression attempts to exploit the task similarity in order to achieve knowledge transfer across related tasks for performance improvement. The application of Gaussian p…
stat.ML2020
Modulating Scalable Gaussian Processes for Expressive Statistical Learning
Haitao Liu, Yew-Soon Ong, Xiaomo Jiang +1
For a learning task, Gaussian process (GP) is interested in learning the statistical relationship between inputs and outputs, since it offers not only the prediction mean but also…
stat.ML2020★ 1 cited
Deep Latent-Variable Kernel Learning
Haitao Liu, Yew-Soon Ong, Xiaomo Jiang +1
Deep kernel learning (DKL) leverages the connection between Gaussian process (GP) and neural networks (NN) to build an end-to-end, hybrid model. It combines the capability of NN to…