Multi-fidelity Gaussian process surrogate modeling for regression problems in physics
One of the main challenges in surrogate modeling is the limited availability of data due to
resource constraints associated with computationally expensive simulations. Multi-fidelity …
resource constraints associated with computationally expensive simulations. Multi-fidelity …
Uncertainty Quantification and Machine Learning Surrogate Models for Multi-Scale High-Performance-Computing Plasma Physics Turbulent Transport Simulations
Y Yudin - 2024 - mediatum.ub.tum.de
This work presents an uncertainty quantification applied to equations for plasma evolution in
a tokamak, focusing on uncertainties in heat transport driven by turbulent processes, solved …
a tokamak, focusing on uncertainties in heat transport driven by turbulent processes, solved …