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Domain generalization (DG) tackles the problem of learning a model that generalizes to data drawn from a target domain that was unseen during training. A major trend in this area consists of learning a domain-invariant representation by minimizing the disc ...
The potential of automatic code generation through Model-Driven Engineering (MDE) frameworks has yet to be realized. Beyond their ability to help software professionals write more accurate, reusable code, MDE frameworks could make programming accessible fo ...
Language has shaped human evolution and led to the desire to endow machines with language abilities. Recent advancements in natural language processing enable us to achieve this breakthrough in human-machine interaction. However, introducing conversational ...
The integration of information technologies into medical systems has led to an increase in digitalization, which results in enormous possibilities, but also challenges in system development. The ever-growing complexity of modern medical devices (MD) requir ...
Code generation is an effective way to drive the complex system development in model-based systems engineering. Currently, different code generators are developed for different modeling languages to deal with the development of systems with multi-domain. T ...
Cyber-physical systems (CPSs) integrate heterogeneous systems and process sensor data using digital services. As the complexity of CPS increases, it becomes more challenging to efficiently formalize the integrated multidomain views with flexible automated ...
Physics-informed machine learning (PIML) is a set of methods and tools that systematically integrate machine learning (ML) algorithms with physical constraints and abstract mathematical models developed in scientific and engineering domains. As opposed to ...
Currently, the fundamental tenets of systems engineering are supported by a model-based approach to minimize risks and avoid design changes in late development stages. The models are used to formalize, analyze, design, optimize, and verify system developme ...
Model-based systems engineering (MBSE) provides an important capability for managing the complexities of system development. MBSE empowers the formalism of system architectures for supporting model-based requirement elicitation, specification, design, deve ...
In this paper, we describe a method to tackle data sparsity and create recommendations in domains with limited knowledge about user preferences. We expand the variational autoencoder collaborative filtering from a single-domain to a multi-domain setting. T ...