Search Results for author:
Found 5 papers, 2 papers with code
SMT 2.0: A Surrogate Modeling Toolbox with a focus on Hierarchical and Mixed Variables Gaussian Processes
The Surrogate Modeling Toolbox (SMT) is an open-source Python package that offers a collection of surrogate modeling methods, sampling techniques, and a set of sample problems.
Control Co-design of a Hydrokinetic Turbine with Open-loop Optimal Control
The optimization formulation incorporates a coupled dynamic-hydrodynamic model to maximize the rotor power efficiency for various time-variant flow profiles.
Machine Learning in Aerodynamic Shape Optimization
We review the applications of ML in ASO to date and provide a perspective on the state-of-the-art and future directions.
Learning High-Dimensional Parametric Maps via Reduced Basis Adaptive Residual Networks
We propose a scalable framework for the learning of high-dimensional parametric maps via adaptively constructed residual network (ResNet) maps between reduced bases of the inputs and outputs.
Gradient-enhanced kriging for high-dimensional problems
They do not scale well with the number of independent variables either due to the increase in the number of hyperparameters that needs to be estimated.
