2 papers
cs.LG2025
$PINN - a Domain Decomposition Method for Bayesian Physics-Informed Neural Networks
Júlia Vicens Figueres, Juliette Vanderhaeghen, Federica Bragone +2
Physics-Informed Neural Networks (PINNs) are a novel computational approach for solving partial differential equations (PDEs) with noisy and sparse initial and boundary data. Altho…
cs.LG2025
Discovering Partially Known Ordinary Differential Equations: a Case Study on the Chemical Kinetics of Cellulose Degradation
Federica Bragone, Kateryna Morozovska, Tor Laneryd +2
The degree of polymerization (DP) is one of the methods for estimating the aging of the polymer based insulation systems, such as cellulose insulation in power components. The main…