Network (knowledge) graphs represent a collection of interlinked entities organized into contexts via linking and semantic metadata. They build a framework for data integration and analysis. Having ...

This repository contains the code for the WiDS lecture "Graph Theory for Data Science, Part III: Characterizing graphs in the real world": Many of the systems we study today can be represented as ...

Attribution Graphs Explorer is a framework for mechanistic interpretability of transformer models based on circuit tracing methods. The toolkit allows researchers to: Extract computational circuits ...

Abstract: Graphical models such as factor graphs allow to model complex systems and help to derive practical detection/estimation algorithms as message passing in the graph. In this paper, we outline ...

Abstract: Expander graphs are highly connected sparse finite graphs. The property of being an expander seems significant in many of these mathematical, computational ...

In this last of three tutorial videos, ARD/SWR's Jürgen Grupp from the Integrated Enterprise Architecture Group shows examples of knowledge graphs in the context of the EBUCorePlus metadata model.

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