twinLab - Probabilistic ML for Engineers#
twinLab™ is a tool for augmenting engineering workflows with Probabilistic ML. It enables you to quickly and easily build real-time emulators of your simulations, experimental set-ups, or sensor networks. Then you can make predictions, perform optimisations, and solve inverse problems.
twinLab™ comes with built-in uncertainty quantification (UQ), which means that even with sparse or noisy data, you can start to understand your design space and emulator confidence. And if you’re starting your programme from scratch, with no data at all, twinLab has you covered with Initial Design Space functionality.
For help, please email: twinlab@digilab.co.uk.
Discover how twinLab’s capabilities can save you time, reduce project costs, and eliminate bottlenecks in your workflow.
Explore the reference guide, examples, and tutorials for the Python Interface, enabling easy workflow integration.
Interested in integrating the power of Probabilistic ML into your software stack? Explore using our RESTful API for language-agnostic usage.
Useful Contacts: Q&A Support | Mailing List