
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:
In this version of UQ[py]Lab we address some minor bugs and general polishing related to the storage of the user credentials to their local machine.
If you haven't already tried this feature you can do so now. Check our quick start guide (section "Storing your UQCloud credentials").
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