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cs.SE2026
Building real-time digital twin instances with Function+Data Flow: user evaluation and extension for iterative pipelines
Eduardo de Conto, Blaise Genest, Arvind Easwaran +2
Digital twins (DTs) increasingly leverage artificial intelligence (AI) and machine learning (ML) pipelines, both to build real-time DTs from high-fidelity simulations and to instan…
cs.SE2025
DesCartes Builder: A Tool to Develop Machine-Learning Based Digital Twins
Eduardo de Conto, Blaise Genest, Arvind Easwaran +2
Digital twins (DTs) are increasingly utilized to monitor, manage, and optimize complex systems across various domains, including civil engineering. A core requirement for an effect…
cs.SE2024
Function+Data Flow: A Framework to Specify Machine Learning Pipelines for Digital Twinning
Eduardo de Conto, Blaise Genest, Arvind Easwaran
The development of digital twins (DTs) for physical systems increasingly leverages artificial intelligence (AI), particularly for combining data from different sources or for creat…