Error-Aware B-PINNs: Improving Uncertainty Quantification in Bayesian Physics-Informed Neural Networks

no code implementations • 14 Dec 2022 • Olga Graf, Pablo Flores, Pavlos Protopapas, Karim Pichara

Physics-Informed Neural Networks (PINNs) are gaining popularity as a method for solving differential equations.

Uncertainty Quantification

Uncertainty Quantification in Neural Differential Equations

no code implementations • NeurIPS Workshop DLDE 2021 • Olga Graf, Pablo Flores, Pavlos Protopapas, Karim Pichara

Uncertainty quantification (UQ) helps to make trustworthy predictions based on collected observations and uncertain domain knowledge.

Uncertainty Quantification