3 papers
cs.LG2024
Graph Neural Ordinary Differential Equations for Coarse-Grained Socioeconomic Dynamics
James Koch, Pranab Roy Chowdhury, Heng Wan +4
We present a data-driven machine-learning approach for modeling space-time socioeconomic dynamics. Through coarse-graining fine-scale observations, our modeling framework simplifie…
cs.LG2024
Learning Neural Differential Algebraic Equations via Operator Splitting
James Koch, Madelyn Shapiro, Himanshu Sharma +2
Differential algebraic equations (DAEs) describe the temporal evolution of systems that obey both differential and algebraic constraints. Of particular interest are systems that co…
physics.flu-dyn2021
Data-Driven Modeling of Nonlinear Traveling Waves
James Koch
Presented is a data-driven Machine Learning (ML) framework for the identification and modeling of traveling wave spatiotemporal dynamics. The presented framework is based on the st…