Context

We develop graphical conditional generative modeling to identify variables that affect the full conditional distribution of quantities of interest—supporting reduced, interpretable digital-twin surrogates.

Abstract

Digital twin modeling, including control and data assimilation under model …

Context

ISOMORPH provides an open, configurable supply-chain digital twin for simulation, dataset release, and forecasting benchmarks in multi-echelon logistics.

Abstract

Open time-series forecasting (TSF) benchmarks cover retail, energy, weather, and traffic, but supply-chain logistics remains …

Digital twins are real-time digital replicas of physical systems that enable simulation, monitoring, and optimization. Unlike traditional models, they are dynamic (continuously updated), bi-directional (inform physical systems), and predictive (enable forecasting).

Technical challenges

To create a …