New Paper Out!

New paper out on thermal predictions in additive manufacturing.

GPyro is a novel thermal model for additive manufacturing processes. In this work, we introduce a Machine Learning model offering fast and reliable predictions for long extrapolation horizons that link the path plan to the evolution of the process-induced thermal fields. Moreover, with GPyro, we can quantify the uncertainty in our predictions and thus bound the expected error with a high probability. We also show how GPyro can be trained from a single experiment within a few seconds.

Check the full paper external page here

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