… Furthermore, since hypernetwork parameters are never … several personalized federated
learning challenges and find that it outperforms previous methods. Finally, since hypernetworks …

… , we propose a personalized federated learning framework with hypernetwork [11] based on
… Since hypernetwork provides a lightweight personalized learning solution which is perfectly …

… we propose a hypernetworkbased federated learning method for personalized CT imaging,
… , which are implemented by an institutionspecific hypernetwork and a global-sharing imaging …

… As an emerging paradigm, federated learning (FL) trains a shared global … hypernetwork
(HN) and a large target network (NN) whose parameters are generated by the hypernetwork. …

… Specifically, at the server side, we introduce a dedicated hypernetwork for each client to
learn the weights of cross-clients’ layers during the pFL training procedure, which is shown to …

… attributed to the inherent personalization of the network. That is, beyond its ability to adapt
to new architectures, HAFL-GHN can also learn a personalized weight prediction according to …

… , we propose a hypernetwork-based physics-driven personalized federated learning method
(… -specific physics-driven hypernetwork and a global-sharing imaging network, respectively. …

… personalized federated learning algorithm based on Hypernetwork, which generates
personalized networks for clients with layered modules, improving the personalized capabilities of …

… Therefore, the personalized federation learning problem of this paper turns to how to establish
a … that adaptively complete the training of federation learning under external conditions. …

… based federated learning framework that learns personalized … personalization mechanism
that maintains personalized self-… a hypernetwork to personalized federated learning, where a …