Function+data flow: a framework to specify machine learning pipelines for digital twinning

• Main Authors: de Conto, Eduardo, Genest, Blaise, Easwaran, Arvind
• Other Authors: College of Computing and Data Science
• Format: Conference or Workshop Item
• Language: English
• Published: 2025
• Subjects: Computer and Information Science; Digital twins; Machine learning pipeline
• Online Access: https://hdl.handle.net/10356/182749; https://dl.acm.org/doi/abs/10.1145/3664646.3664759
• Institution: Nanyang Technological University

The development of digital twins (DTs) for physical systems increasingly leverages artificial intelligence (AI), particularly for combining data from different sources or for creating computationally efficient, reduced-dimension models. Indeed, even in very different application domains, twinning...