RSUQ presents
UQ[py]Lab
Uncertainty Quantification with Python, powered by UQLab
JOIN THE BETAGet StartedLearn More

Uncertainty quantification on the cloud powered by UQLab.

Based on the UQLab platform
  • Cutting-edge technology
  • General purpose UQ software
  • Extremely fast learning curve
  • Reference software in academia
lives on the cloud
  • No need for installation
  • Available everywhere
  • Your analysis stays on the cloud
  • Operating-system independent

What you can do with UQ[py]Lab

Here are some highlights, but there is much more
True vs. PCE approximation of a computational model
Polynomial Chaos Expansions

Polynomial chaos expansions (PCE), one of the most powerful and versatile surrogate models available today

  • Non-intrusive PCE facilities
  • State-of-the-art sparse regression solvers, including least angle regression, subspace pursuit, Bayesian compressing sensing and much more
  • Support for classical polynomials, as well as polynomials orthogonal to user-defined input distributions
  • Support also fully data-driven, arbitrary PCE
Sobol' sensitivity indices calculated with Monte-Carlo simulation vs. metamodel-based
State-of-the art sensitivity analysis

Sensitivity analysis can identify the driving factors that most influence the response of a model

  • Approximation- and simulation- based methods
  • Advanced variance decomposition techniques (e.g. Sobol' indices)
  • Support for metamodel-based sensitivity analysis
  • Support for sensitivity analysis of dependent input variables
Effect of introducing a copula with fixed marginals
Advanced probabilistic modelling

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.

  • Support for many common marginal distributions
  • Support for standard copulas, as well as complex vine-copula constructions
  • Fully automatic inference of both marginal distributions and copula
  • Advanced sampling schemes, including latin hypercube sampling, quasi-random sequences

how to get the beta

Our team at RSUQ has been working hard on ironing out bugs and providing a UQ[py]Lab user experience that resembles as closely as possible the UQLab one.

We believe that UQ[py]Lab is now mature enough to start inviting external beta testers. You are welcome to apply regardless of your current affiliation, be it academic or industrial.

However, we would appreciate it if you let us know about what you are looking forward to test once you are included in the UQ[py]Lab beta testing phase.

To apply for beta-testing UQ[py]Lab just press the button below, fill in the form and follow the instructions.
REGISTER  FOR THE BETAAlready Registered!

Contact us

UQ[py]Lab support

Please use this form to contact us if you need support for the installation and/or operation of UQ[py]Lab.

Address

Chair of Risk, Safety and Uncertainty Quantification​
Stefano Franscini-Platz 5
CH-8093 Zurich
Switzerland

Contact form

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Plans & Pricing

No credit card required. No risk, 30-day money back guarantee!

Starter

$15 /month
500 Data Points
1 Team Member
Email Support
IOS and Android App
Customizable Dashboard
Metric API
Choose Plan

Professional

$30 /month
2000 Data Points
1 Team Member
Email Support
IOS and Android App
Customizable Dashboard
Metric API
Choose Plan

Startup

$75 /month
5000 Data Points
3 Team Member
Email Support
IOS and Android App
Customizable Dashboard
Metric API
Choose Plan

Business

$250 /month
15000 Data Points
10 Team Member
Priority Support
IOS and Android App
Customizable Dashboard
Metric API
Choose Plan
Need more Data Points or Team Members? Please contact us.

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