Towards Sustainability Model Cards: A DSL for specifying AI’s Environmental Impact
We propose a new Domain-Specific Language to precisely define the sustainability aspects of an ML model (including the energy costs for its different tasks) that can be exported as an extended Model Card
The perfect three-way: data, models and AI
In the last decade, we have witnessed an explosion of research on new architectures, training methods, fine-tuning strategies, etc. for machine learning (ML). But we are now entering a new phase where all these new approaches are becoming a commodity. Platforms like...
Guidelines for Quality Management of Research Artifacts in Model-Driven Engineering
In Model-Driven Engineering, openly providing research artifacts has become vital, e.g. for the broader adoption of AI techniques. We present you a set of guidelines designed as a toolkit to support researchers in creating, sharing, and maintaining artifacts in MDE research.
Modeling, verifying and generating embedded software with Dezyne
Our review of Dezyne, a great tool to quickly model, verify and generate component-based software.
Diverse scenario exploration in model finders using graph kernels and clustering
Clustering of model instances by using graph kernels. Make sure you test your models with the most diverse set of examples!
The low-code handbook
Modeling: all you need to know
Recent Comments