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Found 8 papers, 2 papers with code
AI-Enabled Software and System Architecture Frameworks: Focusing on smart Cyber-Physical Systems (CPS)
Therefore, they failed to address the architecture viewpoints and views responsive to the concerns of the data science community.
Model-Driven Quantum Federated Learning (QFL)
Recently, several studies have proposed frameworks for Quantum Federated Learning (QFL).
MDE for Machine Learning-Enabled Software Systems: A Case Study and Comparison of MontiAnna & ML-Quadrat
In this paper, we propose to adopt the MDE paradigm for the development of Machine Learning (ML)-enabled software systems with a focus on the Internet of Things (IoT) domain.
Enabling Automated Machine Learning for Model-Driven AI Engineering
Developing smart software services requires both Software Engineering and Artificial Intelligence (AI) skills.
MDE4QAI: Towards Model-Driven Engineering for Quantum Artificial Intelligence
Over the past decade, Artificial Intelligence (AI) has provided enormous new possibilities and opportunities, but also new demands and requirements for software systems.
A Model-Driven Approach to Machine Learning and Software Modeling for the IoT
In particular, we implement the proposed approach, called ML-Quadrat, based on ThingML, and validate it using a case study from the IoT domain, as well as through an empirical user evaluation.
ML-Quadrat & DriotData: A Model-Driven Engineering Tool and a Low-Code Platform for Smart IoT Services
In this paper, we present ML-Quadrat, an open-source research prototype that is based on the Eclipse Modeling Framework (EMF) and the state of the art in the literature of Model-Driven Software Engineering (MDSE) for smart Cyber-Physical Systems (CPS) and the Internet of Things (IoT).
Supporting AI Engineering on the IoT Edge through Model-Driven TinyML
We focus on a sub-discipline of AI, namely Machine Learning (ML) and propose the delegation of data analytics and ML to the IoT edge.
