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Found 3 papers, 1 papers with code
Personalized Federated Learning of Probabilistic Models: A PAC-Bayesian Approach
Personalized federated learning (PFL) goes one step further by adapting the global model to each client, enhancing the model's fit for different clients.
Physically Consistent Neural ODEs for Learning Multi-Physics Systems
Since IPHS models are consistent with the first and second principles of thermodynamics by design, so are the proposed Physically Consistent NODEs (PC-NODEs).
A unified framework for Hamiltonian deep neural networks
Training deep neural networks (DNNs) can be difficult due to the occurrence of vanishing/exploding gradients during weight optimization.
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