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Found 4 papers, 2 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.
SIMBa: System Identification Methods leveraging Backpropagation
This manuscript details the SIMBa toolbox (System Identification Methods leveraging Backpropagation), which uses well-established Machine Learning tools for discrete-time linear multi-step-ahead state-space System Identification (SI).
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.
