
In this version of UQ[py]Lab many updates have been introduced under the hood.
Major new features:
Make sure to also check out new Contributors and User Manuals pages!
We are happy to report that during the ongoing open beta of UQ[py]Lab more than 300 users have already registered and tested it.
In this version of UQ[py]Lab we introduce logging control, i.e. control of the verbosity of each command.
Furthermore, we fixed some bugs. Notable mentions:
Polynomial chaos expansions (PCE), one of the most powerful and versatile surrogate models available today
Sensitivity analysis can identify the driving factors that most influence the response of a model
Probabilistic modelling lies at the core of uncertainty quantification. Full support for complex probabilistic models based on copula and marginal representation. Powerful data-driven inference module.
Chair of Risk, Safety and Uncertainty Quantification
Stefano Franscini-Platz 5
CH-8093 Zurich
Switzerland