Structural Inference of Networked Dynamical Systems with Universal Differential Equations. - James Koch; Zhao Chen; Aaron Tuor; Ján Drgona; Draguna L. Vrabie (CoRR, 2022)

Physics-informed Machine Learning of Parameterized Fundamental Diagrams. - James Koch; Thomas Maxner; Vinay Amatya; Andisheh Ranjbari; Chase Dowling (CoRR, 2022)

Data-Driven Invertible Neural Surrogates of Atmospheric Transmission. - James Koch; Brenda Forland; Bruce Bernacki; Timothy Doster; Tegan Emerson (IGARSS, 2024)

Stars: Sensor-Agnostic Transformer Architecture for Remote Sensing. - Ethan King; Jaime Rodriguez; Diego Llanes; Timothy Doster; Tegan Emerson; James Koch (WHISPERS, 2024)

Neural Differential Algebraic Equations. - James Koch; Madelyn Shapiro; Himanshu Sharma; Draguna L. Vrabie; Ján Drgona (CoRR, 2024)

Graph Neural Ordinary Differential Equations for Coarse-Grained Socioeconomic Dynamics. - James Koch; Pranab Roy Chowdhury; Heng Wan; Parin Bhaduri; Jim Yoon; Vivek Srikrishnan; W. Brent Daniel (CoRR, 2024)

Neural lumped parameter differential equations with application in friction-stir processing. - James Koch; WoongJo Choi; Ethan King; David Garcia; Hrishikesh Das; Tianhao Wang 012; Ken Ross; Keerti Kappagantula (J. Intell. Manuf., 2025)

First Contact: Data-driven Friction-Stir Process Control. - James Koch; Ethan King; WoongJo Choi; Megan Ebers; David Garcia; Ken Ross; Keerti Kappagantula (CoRR, 2025)