For many applications in science and engineering a machine learning (ML) model must be able to output values as a function of another variable. For example:
A ML model trained on CFD combustion simulation results may need to predict pressure as a function of crank angle, rather than for example a single scalar output such as maximum pressure across the entire cycle.
A ML model trained on multibody dynamics simulation results may need to predict acceleration as a function of time.
A ML model trained of an acoustics simulation may need to predict as a function of frequency.
SmartUQ currently offers a Functional Response Emulator (An emulator is a predictive model) capable of handling such problems. Join us for this webinar to learn more and see a demo.
