For many applications in science and engineering a machine learning (ML) model must be able to make predictions for systems with a large number of inputs. However, as the number of inputs to a problem increases common modeling techniques such as Gaussian process (GP) modeling suffer from numerical issues and extremely long training times.
SmartUQ has developed a unique GP based model, the Active Dimension Hybrid Emulator (An emulator is a predictive model), specifically designed for efficiently training problems with large numbers of inputs. Join us for this webinar to learn more and see a demo.
