by The digiLab Team
Updated 11 March 2024
digiLab Newsletter: Issue 4
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The Kernel Cookbook
Kernels play a very important role in determining the characteristics of both the prior and posterior distributions of the Gaussian Process. But with many to choose from, and with countless variations and combinations, how do we choose the right one?
Ana's tutorial video will give you a proper understanding of the different kernels that exist, their advantages, limitations and applications, and how to combine them.
twinLab Feature Release - Initial Design Spaces
If you're building a model or set of experiments from scratch, sometimes you need a particular scheme of sampling to effectively span the entire design space at hand. You can now do this with a simple function call in twinLab.
We've produced an example article showing you how to get recommendations of points to be sampled in the design space - before training an emulator.
digiLab Joins U.S. DIII-D National Fusion Facility
digiLab has begun efforts to advance fusion in the US, by joining the DIII-D National Fusion Facility, a U.S Department of Energy user facility. As a member of this facility that houses a world-class research tokamak, digiLab can now work with data and scientists from the facility to solve some of the hardest challenges in fusion.
What's more, the experimental DIII-D facility can be used as a testbed for digiLab to explore its capabilities in machine learning for fusion.
Probabilistic ML with twinLab
twinLab is already being used to solve next-generation engineering and sustainability challenges at organisations like the UKAEA, Airbus, and Rolls-Royce. Our vision with twinLab is to help more people and organisations to use probabilistic ML.
Just hit "Try twinLab" at the top-right, or reply to this email, and we'll set you up with an API key, the documentation, and some example solutions.
Alternatively, if you've got a particular data challenge, book a free call with one of our solution engineers.
Featured Posts
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