Browsing Faculty of Engineering by Subject "Kernel learning"
Now showing items 1-1 of 1
-
Performance analysis of meta-learning based bayesian deep kernel transfer methods for regression tasks
(IEEE, 2023)Meta-learning aims to apply existing models on new tasks where the goal is 'learning to learn' so that learning from a limited amount of labeled data or learning in a short amount of time is possible. Deep Kernel Transfer ...
Share this page