Data-Driven Wind Farm Optimization Incorporating Effects of Turbulence Intensity. - Christiane Adcock; Ryan N. King (ACC, 2018)

GANISP: a GAN-assisted Importance SPlitting Probability Estimator. - Malik Hassanaly; Andrew Glaws; Ryan N. King (CoRR, 2021)

Bi-fidelity Modeling of Uncertain and Partially Unknown Systems using DeepONets. - Subhayan De; Malik Hassanaly; Matthew J. Reynolds; Ryan N. King; Alireza Doostan (CoRR, 2022)

Adversarial sampling of unknown and high-dimensional conditional distributions. - Malik Hassanaly; Andrew Glaws; Karen Stengel; Ryan N. King (J. Comput. Phys., 2022)

PINN surrogate of Li-ion battery models for parameter inference. Part I: Implementation and multi-fidelity hierarchies for the single-particle model. - Malik Hassanaly; Peter J. Weddle; Ryan N. King; Subhayan De; Alireza Doostan; Corey R. Randall; Eric J. Dufek; Andrew M. Colclasure; Kandler Smith (CoRR, 2023)

PINN surrogate of Li-ion battery models for parameter inference. Part II: Regularization and application of the pseudo-2D model. - Malik Hassanaly; Peter J. Weddle; Ryan N. King; Subhayan De; Alireza Doostan; Corey R. Randall; Eric J. Dufek; Andrew M. Colclasure; Kandler Smith (CoRR, 2023)

Super Resolution for Renewable Energy Resource Data With Wind From Reanalysis Data (Sup3rWind) and Application to Ukraine. - Brandon N. Benton; Grant Buster; Pavlo Pinchuk; Andrew Glaws; Ryan N. King; Galen Maclaurin; Ilya Chernyakhovskiy (CoRR, 2024)

Tackling extreme urban heat: a machine learning approach to assess the impacts of climate change and the efficacy of climate adaptation strategies in urban microclimates. - Grant Buster; Jordan Cox; Brandon N. Benton; Ryan N. King (CoRR, 2024)