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Authors
Zia, Muhammad Saad
Houpert, Corentin
Anjum, Ashiq
Liu, Lu
Conway, Anthony
Peña-Rios, Anasol
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Funding
Funding for this research was provided by:
AI-driven Digital Twins for Net Zero (EP/Y00597X/1)
AI-driven Digital Twins for Net Zero (EP/Y00597X/1)
AI-driven Digital Twins for Net Zero (EP/Y00597X/1)
Clinical Care (EP/Y018281/1)
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Article History
Received: 19 March 2025
Revised: 19 March 2025
Accepted: 26 May 2025
First Online: 10 July 2025
Declarations
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: The IP for this work is owned by BT PLC, and as part of the agreement, the patent for this work has been filed before submitting the document to the journal.
: The experiments were performed on data not related to living beings. No human beings and animals were involved in conducting the experiments. Thus, approval from an ethical committee is not required.
: No living beings are involved in conducting the experiments for this research. Thus, consent to participate is not required.
: The authors involved in conducting this research give their consent for the publication of the article titled “Physics Encoded Blocks in Residual Neural Network Architectures for Digital Twin Models”.
: The code has been made available on GitHub.
