Learn how to choose the right scale for a graph based on the type of data, the purpose of the graph, and the audience you want to reach. See examples and tips.

Graph neural networks (GNNs) are powerful machine learning models that can capture the complex patterns and relationships in graph data, such as social networks, molecular structures, and ...

Graphs that are not drawn to scale mislead the reader. This post shows another example of a graph where the visual representation of the numbers is not proportional to the numbers themselves.

The graph can be used to convert any value from one scale to the other. For example, 4 miles is approximately 6.4 kilometres and 4 kilometres is approximately 2.5 miles. Another way to plot the ...

Remarkable progress has been achieved for salient object detection based on deep learning. However, most of the previous works have the issues of how to extract more effective information from ...

Katana Graph, a startup that helps businesses analyze and manage unstructured data at scale, today announced a $28.5 million series A round led by Intel Capital.. Katana Graph was founded by ...

With the rapid emergence of graph representation learning, the construction of new large-scale datasets are necessary to distinguish model capabilities and accurately assess the strengths and ...