Ryan N. King

According to our database, Ryan N. King authored at least 13 papers between 2018 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

A Conditional Diffusion Model for Building Energy Modeling Workflows.

Saumya Sinha, Alexandre Cortiella, Rawad El Kontar, Andrew Glaws, Ryan N. King, Patrick Emami

CoRR, November, 2025

Adaptive Computing for Scale-Up Problems.

Kevin Patrick Griffin, Hilary Egan, Marc T. Henry de Frahan, Juliane Mueller, Deepthi Vaidhynathan, Dylan Wald, Rohit Chintala, Olga A. Doronina, Hariswaran Sitaraman, Ethan Young, Ryan N. King, Jibonananda Sanyal, Marc Day, Ross E. Larsen

Comput. Sci. Eng., 2025

Designing Future Energy Systems With Generative AI.

Andrew Glaws, Ryan N. King, Patrick Emami, Grant Buster, Brandon N. Benton, Xiangyu Zhang, Ahmed S. Zamzam, Venkatesh Venkataramanan, Richard Macwan

Comput. Sci. Eng., 2025

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

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

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

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

2022

Adversarial sampling of unknown and high-dimensional conditional distributions.

Malik Hassanaly, Andrew Glaws, Karen Stengel, Ryan N. King

J. Comput. Phys., 2022

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

2021

GANISP: a GAN-assisted Importance SPlitting Probability Estimator.

Malik Hassanaly, Andrew Glaws, Ryan N. King

CoRR, 2021

Visualization of Multi-Fidelity Approximations of Stochastic Economic Dispatch.

Kinshuk Panda, Ryan N. King, Jonathan Maack, Ignas Satkauskas, Kristi Potter

Proceedings of the e-Energy '21: The Twelfth ACM International Conference on Future Energy Systems, Virtual Event, Torino, Italy, 28 June, 2021

2019

A block-random algorithm for learning on distributed, heterogeneous data.

Prakash Mohan, Marc T. Henry de Frahan, Ryan N. King, Ray W. Grout

CoRR, 2019

2018

Data-Driven Wind Farm Optimization Incorporating Effects of Turbulence Intensity.

Christiane Adcock, Ryan N. King

Proceedings of the 2018 Annual American Control Conference, 2018