Abstract: Recent advances in Graph Convolutional Neural Networks (GCNNs) have shown their efficiency for nonEuclidean data on graphs, which often require a large amount of labeled data with high cost.

Agile rituals are great, but without tracking constraints and dependencies live, your transformation will stall.

MATH 1050, College Algebra, QL, 4 credits. Functions: graphs, transformations, combinations and inverses. Polynomial, rational, exponential, logarithmic functions and applications. Systems of ...

In this paper, we investigate the transformation phenomenon of the first-order breather and the second-order breather. First, we obtain the 2-solitary wave and 4-solitary wave solutions of the (2 + 1) ...

Henshin is a state of the art model transformation language for the Eclipse Modeling Framework. Henshin supports both direct transformations of EMF single model instances (endogenous transformations), ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Dissolved organic matter (DOM) is a complex mixture of thousands of natural molecules ...

Many factors force businesses to be flexible, nimble, and, above all, innovative. In today’s business landscape, it is imperative to innovate on a regular basis. And it doesn’t just happen out of the ...

The Graph Transformation Framework is as the name suggests, all about graphs and their transformation into desired target models. It provides different modules, like ... There is no general getting ...

Chair of Computational Modeling and Simulation, TUM School of Engineering and Design, Technical University of Munich, Munich, Germany Capturing human knowledge underlying the design and engineering of ...